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With the rise of data-driven recruitment, it is imperative for each recruitment tool, including candidate sourcing and screening tools, to integrate with Applicant Tracking Systems (ATS) for enabling centralized data management for end users.
However, there are hundreds of ATS applications available in the market today. To integrate with each one of these applications with different ATS APIs is next to impossible.
That is why more and more recruitment tools are looking for a better (and faster) way to scale their ATS integrations. Unified ATS APIs are one such cost-effective solution that can cut down your integration building and maintenance time by 80%.
Before moving on to how companies can leverage unified ATS API to streamline candidate sourcing and screening, let’s look at the workflow and how ATS API helps.
Here’s a quick snapshot of the candidate sourcing and screening workflow:
Posting job requirements/ details about open positions to create widespread outreach about the roles you are hiring for.
Collecting and fetching candidate profiles/ resumes from different platforms—job sites, social media, referrals—to create a pool of potential candidates for the open positions.
Taking out all relevant data—skills, relevant experience, expected salary, etc. —from a candidate’s resume and updating it based on the company’s requirement in a specific format.
Eliminating profiles which are not relevant for the role by mapping profiles to the job requirements.
Conducting a preliminary check to ensure there are no immediate red flags.
Setting up and administering assessments, setting up interviews to ensure role suitability and collating evaluation for final decision making.
Sharing feedback and evaluation, communicating decisions to the candidates and continuing the process in case the position doesn’t close.
Here are some of the top use cases of how ATS API can help streamline candidate sourcing and screening.
All candidate details from all job boards and portals can be automatically collected and stored at one centralized place for communication and processing and future leverage.
ATS APIs ensure real time, automated candidate profile import, reducing manual data entry errors and risk of duplication.
ATS APIs can help automate screening workflows by automating resume parsing and screening as well as ensuring that once a step like background checks is complete, assessments and then interview set up are triggered automatically.
ATS APIs facilitate real time data sync and event-based triggers between different applications to ensure that all candidate information available with the company is always up to date and all application updates are captured ASAP.
ATS APIs help analyze and draw insights from ATS engagement data — like application rate, response to job postings, interview scheduling — to finetune future screening.
ATS API can further integrate with other assessment, interview scheduling and onboarding applications enabling faster movement of candidates across different recruitment stages.
ATS API integrations can help companies with automated, personalized and targeted outreach and candidate communication to improve candidate engagement, improve hiring efficiency and facilitate better employer branding.
Undoubtedly, using ATS API integration can effectively streamline the candidate sourcing and screening process by automating several parts of the way. However, there are several roadblocks to integrating ATS APIs at scale because of which companies refrain from leveraging the benefits that come along. Try our ROI calculator to see how much building integrations in-house can he.
In the next section we will discuss how to solve the common challenges for SaaS products trying to scale and accelerate their ATS integration strategy.
Let's discuss how the roadblocks can be removed with unified ATS API: just one API for all ATS integrations. Learn more about unified APIs here
When data is being exchanged between different ATS applications and your system, it needs to be normalized and transformed. Since the same details from different applications can have different fields and nuances, chances are if not normalized well, you will end up losing critical data which may not be mapped to specific fields between systems.
This will hamper centralized data storage, initiate duplication and require manual mapping not to mention screening workflow disruption. At the same time, normalizing each data field from each different API requires developers to understand the nuances of each API. This is a time and resource intensive process and can take months of developer time.
Unified APIs like Knit help companies normalize different ATS data by mapping different data schemas from different applications into a single, unified data model for all ATS APIs. Data normalization takes place in real time and is almost 10X faster, enabling companies to save tech bandwidth and skip the complex processes that might lead to data loss due to poor mapping.
Bonus: Knit also offers an custom data fields for data that is not included in the unified model, but you may need for your specific use case. It also allows you to to request data directly from the source app via its Passthrough Request feature. Learn more
Second, some ATS API integration has a polling infrastructure which requires recruiters to manually request candidate data from time to time. This lack of automated data updation in real time can lead to delayed sourcing and screening of applicants, delaying the entire recruitment process. This can negatively impact the efficiency that is expected from ATS integration.
Furthermore, Most ATS platforms receive 1000s of applications in a matter of a few minutes. The data load for transfer can be exceptionally high at times, especially when a new role is posted or there is any update.
As your number of integrated platforms increases, managing such bulk data transfers efficiently as well as eliminating delays becomes a huge challenge for engineering teams with limited bandwidth
Knit as a unified ATS API ensures that you don’t lose out on even one candidate application or be delayed in receiving them. To achieve this, Knit works on a webhooks based system with event-based triggers. As soon as an event happens, data syncs automatically via webhooks.
Read: How webhooks work and how to register one?
Knit manages all the heavy lifting of polling data from ATS apps, dealing with different API calls, rate limits, formats etc. It automatically retrieves new applications from all connected ATS platforms, eliminating the need to make API calls or manual data syncs for candidate sourcing and screening.
At the same time, Knit comes with retry and resiliency guarantees to ensure that no application is missed irrespective of the data load. Thus, handling data at scale.
This ensures that recruiters get access to all candidate data in real time to fill positions faster with automated alerts as and when new applications are retrieved for screening.
Since the ATS and other connected platforms have access to sensitive data, protecting candidate data from attacks, ensuring constant monitoring and right permission/ access is crucial yet challenging to put in practice.
Knit unified ATS API enables companies to effectively secure the sensitive candidate data they have access to in multiple ways.
Finally, ATS API integration can be a long drawn process. It can take 2 weeks to 3 months and thousands of dollars to build integration with just a single ATS provider.
With different end points, data models, nuances, documentation etc. ATS API integration can be a long deployment project, diverting away engineering resources from core functions.
It’s not uncommon for companies to lose valuable deals due to this delay in setting up customer requested ATS integrations.
Furthermore, the maintenance, documentation, monitoring as well as error handling further drains engineering bandwidth and resources. This can be a major deterrent for smaller companies that need to scale their integration stack to remain competitive.
A unified ATS API like Knit allows you to connect with 30+ ATS platforms in one go helping you expand your integration stack overnight.
All you have to do is embed Knit’s UI component into your frontend once. All heavy lifting of auth, endpoints, credential management, verification, token generations, etc. is then taken care of by Knit.
Fortunately, companies can easily address the challenges mentioned above and streamline their candidate sourcing and screening process with a unified ATS API. Here are some of the top benefits you get with a unified ATS API:
Once you have scaled your integrations, it can be difficult to monitor the health of each integration and stay on top of user data and security threats. Unified API like Knit provides a detailed Logs and Issues dashboard i.e. a one page overview of all your integrations, webhooks and API calls. With smart filtering options for Logs and Issues, Knit helps you get a quick glimpse of the API's status, extract historical data and take necessary action as needed.
Along with Read APIs, Knit also provides a range of Write APIs for ATS integrations so that you can not only fetch data from the apps, you can also update the changes — updating candidate’s stage, rejecting an application etc. — directly into the ATS application's system. See docs
For an average SaaS company, each new integration takes about 6 weeks to 3 months to build and deploy. For maintenance, it takes minimum of 10 developer hours per week. Thus, building each new integration in-house can cost a SaaS business ~USD 15,000. Imagine doing that for 30+ integrations or 200!
On the other hand, by building and maintaining integrations for you, Knit can bring down your annual cost of integrations by as much as 20X. Calculate ROI yourself
In short, an API aggregator is non negotiable if you want to scale your ATS integration stack without compromising valuable in-house engineering bandwidth.
Fetch job IDs from your users Applicant Tracking Systems (ATS) using Knit’s job data models along with other necessary job information such as departments, offices, hiring managers etc.
Use the job ID to fetch all and individual applicant details associated with the job posting. This would give you information about the candidate such as contact details, experience, links, location, experience, current stage etc. These data fields will help you screen the candidates in one easy step.
Next is where you take care of screening activities on your end after getting required candidate and job details. Based on your use case, you parse CVs, conduct background checks and/or administer assessment procedures.
Once you have your results, you can progmmatically push data back directly within the ATS system of your users using Knit’s write APIs to ensure a centralized, seamless user experience. For example, based on screening results, you can —
Thus, Knit ensures that your entire screening process is smooth and requires minimum intervention.
If you are looking to quickly connect with 30+ ATS applications — including Greenhouse, Lever, Jobvite and more — get your Knit API keys today.
You may talk to our one of our experts to help you build a customized solution for your ATS API use case.
The best part? You can also make a specific ATS integration request. We would be happy to prioritize your request.
Today, recruitment without ATS applications seems almost impossible. From candidate sourcing and screening to communication and onboarding — every part of the recruitment workflow is tied to ATS apps.
Research shows that 78% of recruiters using an ATS report that it has improved the quality of the candidates they hire.
Hiring qualified talent for an organization can be a resource intensive and long drawn process. The entire recruitment workflow has multiple steps and layers, which when accomplished manually can be extremely time consuming. However, companies which leverage recruitment workflow automation by using ATS APIs can save 100s of hours spent in heavy lifting.
Let’s start with understanding the various stages of recruitment workflow and how automation with ATS APIs can help.
The first step involves creating job requisitions based on hiring needs across different teams. This is followed by creating appropriate job descriptions and posting on job boards to attract candidates.
With ATS APIs, this entire process can be automated. ATS APIs come with pre-defined templates to create job requisitions and job descriptions. They also have integrations with leading job boarding to facilitate automatic posting and role promotion of job boards.
Next, most recruitment professionals focus on collecting data on candidate profiles from different job boards. Then, they engage in screening and shortlisting the resumes following a manual process, which takes a long time.
ATS APIs automate the collection of candidate data, resume and other basic information. It goes a step beyond with resume parsing to automate extraction of relevant candidate data from the resume and facilitate storage in a ready to use format for easy screening.
Once the screening is complete, interview scheduling for the shortlisted candidates is the next step. Manually, the process requires a lot of back and forth with interviewers and interviewees, managing schedules, sending invitations and reminders, etc.
ATS APIs led automation takes care of all scheduling struggles and automates the process of sending invitations, reminders and other candidate communication in the process.
Scheduling interviews/ tests is followed by conducted assessments to gauge the candidate's aptitude, skills, knowledge, personality and cognitive abilities for the role.
ATS APIs can easily automate test assessment via online proctored solutions and even record scores and present it to the decision makers in a streamlined and easy to understand format.
When it comes to decision making, ATS APIs can collate evaluation, assessment results and feedback of all candidates and even rank them based on comprehensive scores to help decision makers with data-driven insights on the best candidate for the role.
Once a candidate has been selected, the ATS API can automatically send the offer letter based on pre-defined templates. Acceptance of the offer letter by the candidate can automatically trigger document signing digitally, thereby automating the entire onboarding process. Bi-directional data sync will ensure that all steps of employee onboarding are conducted automatically.
An ATS API also enables recruitment professionals to automatically capture, manage and update all the relevant information about the candidate, application and status in a common platform, which can be accessed as and when needed.
Throughout the recruitment workflow, there are several touchpoints with the candidate. ATS API: can help recruitment professionals with personalized communication templates for candidates based on their application status, interview performance, feedback, etc.
Finally, the ATS API can provide recruitment professionals with key data points and metrics to gauge recruitment performance. Metrics like time to hire, source, open positions, candidate diversity, interview to hire ratio, can all be collated in one report by the ATS API and presented.
With understanding of the recruitment workflow, let’s understand the process of automating the same with ATS API.
To begin with, you need to understand the recruitment stages in your organization and identify the ones which require a lot of heavy lifting and can be automated. For instance, while conducting the interviews cannot be automated, scheduling them and compiling the feedback and evaluation can be. Thus, identify the stages to automate and what benefits you seek to achieve as a result of automation.
There are multiple ATS APIs in the market today. While each one of them comes with multiple functionalities across the recruitment workflow, some are likely to be better over others for particular use cases. Therefore, to leverage automation with ATS API, choose the ones that best suit your industry and requirements. You might even choose multiple ATS APIs and integrate them to your system for different purposes, while also integrating one with another.
Once you have selected the ATS APIs, it’s time to get into the technical aspects of getting the integration in place. To integrate the ATS API, you need to get access to specific credentials and authentication from the ATS provider. These include API key, access tokens, client ID, client secret, endpoints, etc. Once you have these, only then can the integration process begin. Also, ensure you understand the authentication process well.
Once you have the necessary credentials, get started with the integration. This will require coding and engineering effort as you will be building the integration from scratch. Understand the data models, endpoints, authorization by going through the API documentation for each ATS API you choose. Simultaneously get started with data mapping, authentication, error handling, etc. followed by testing to gauge the effectiveness of your integration. Each integration can take anywhere between a few weeks to a few months.
Post integration, you need to keep track of your data exchange and transformation process. Ensure that data synchronization is happening as per your expectations. Your need to keep track of unstable APIs or any updates in the same, error logging challenges, expiry or deactivation of webhooks, management of large data volume, among others. At the same time, monitor any security threats or unauthorized access push.
Finally, optimize your ATS API integration process. Identify the major challenges from the maintenance and management standpoint and focus on fixing the issues to create a better integration experience for your teams.
While using multiple ATS APIs to power different functionalities is enticing, it can be challenging and a major burden on your engineering and other teams. Here are a few limitations that might face while trying to integrate different ATS API for recruitment workflow automation.
Each ATS API comes with different data fields, documentation and processes that need to be followed for integration. Integrating each one requires a steep learning curve for the engineering team. From a resource standpoint, each ATS API integration can take an average of four weeks, costing ~USD 10K. As you scale, there is an exponential time and monetary cost that comes along, which is applicable to each API you add. After a certain time, chances are that the costs and efforts associated with integration scale will significantly surpass the savings and benefits from automation.
Each API, even within the same category of ATS will have different data models. For instance, the field of candidate name may be categorized as cand_name for one ATS API, while candidate_name for another one. To ensure that data from all APIs is consolidated for processing, you need to engage in data normalization and data transformation to process the data from different ATS APIs.
Next, data synchronization in real time can be a big challenge. If you are using a polling infrastructure, you will have to request data sync time and again, that too across multiple APIs. At the same time, data sync can be a challenge with scalability, when the data load becomes unmanageable. The inability to facilitate real time data synchronization can lead to delays in the entire recruitment process or exclusion of applications during a particular round.
Error handling, monitoring and management is extremely resource intensive. It is extremely important to maintain the health of your integrations, by constantly logging their performance. It is important to keep track of API calls, log errors, data sync requests, etc. This is required to catch any potential errors early on and manage integrations better. However, monitoring each API for every second is manually very burdensome.
Compliance and security is a big challenge when it comes to integrations. Since you are dealing with a lot of personal data, you need to be on your toes when it comes to security. At the same time, each API will have a different authentication methodology as well as separate policies that you need to keep pace with.
Finally, you might need custom workflows from your ATS APIs, especially during data exchange between them. Building these custom workflows can be an engineering nightmare, let alone maintaining and monitoring them.
Don’t get apprehensive about using different ATS APIs for automating your recruitment workflows. A unified API like Knit can help you integrate different ATS APIs effortlessly and in less than half the time. Here are the top benefits of using a unified API.
Unified API enables you to scale product integrations faster. You can easily add hundreds of ATS applications to your systems by just learning about the unified API. You no longer have to go through the API documentation of multiple applications or understand the nuances, processes, etc. It is highly time and cost effective from a scale and optimization lens.
A unified API like Knit can provide you with a common data model. You can easily eliminate the data transformation nuances and complex processes for different APIs. It enables you to map different data schemas from different ATS applications into a single, unified data model as normalized data. In addition, you can also incorporate custom data fields i.e. you can access any non-standard data you need, which may not be included in the common ATS data model.
Following a webhooks based event driven architecture, unified APIs like Knit ensure real time data sync. Without the need for any polling infrastructure or request, Knit facilitates assured real time data sync, irrespective of the data load. Furthermore, it also sends automatic notifications and alerts when new data has been updated.
Knit, as a unified API, helps companies leveraging ATS integration ensure high levels of security. It is the only unified API which doesn’t store a copy of the customer data. Furthermore, being 100% webhook-based architecture, it facilitates greater security. You don’t have to navigate through different security policies for different APIs and can access OAuth, API key or a username-password based authentication. Finally, all data with our unified API is doubly encrypted, when in rest and when in transit.
With a unified API like Knit, integration management also becomes seamless. It enables you to monitor and manage all ATS integrations using a detailed Logs, Issues, Integrated Accounts and Syncs page. Furthermore, the fully searchable Logs keep track of API calls, data syncs and requests and status of each webhook registered. This effectively streamlines integration management and error resolution 5x faster.
Recruitment professionals and leaders involved in different stages of the recruitment lifecycle can leverage ATS integrations to automate their workflows. With the right ATS API, each stage of the recruitment workflow can be automated to a certain extent to save time and effort. However, building and maintaining different ATS API can be challenging with issues of scale, data transformation, synchronization, etc. Fortunately, with a unified API, companies can address these issues for seamless scalability, data transformation with a unified data model supported by custom data fields, high security with double encryption, webhook architecture for real time data sync, irrespective of workload and easy integration management with detailed logs, issues, etc. Get started with a unified API to integrate all your preferred ATS applications to automate and streamline your recruitment workflows.
Marketing automation tools are like superchargers for marketers, propelling their campaigns to new heights. Yet, there's a secret ingredient that can take this power to the next level: the right audience data.
What better than an organization’s CRM to power it?
The good news is that many marketing automation tools are embracing CRM API integrations to drive greater adoption and results. However, with the increasing number of CRM systems underplay, building and managing CRM integrations is becoming a huge challenge.
Fortunately, the rise of unified CRM APIs is bridging this gap, making CRM integration seamless for marketing automation tools. But, before delving into how marketing automation tools can power integrations with unified CRM APIs, let’s explore the business benefits of CRM APIs.
Here’s a quick snapshot of how CRM APIs can bring out the best of marketing automation tools, making the most of the audience data for customers.
Research shows that 72% of customers will only engage with personalized messaging. CRM integration with marketing automation tools can enable the users to create personalized messaging based on customer segmentation.
Users can segment customers based on their likelihood of conversion and personalize content for each campaign. Slicing and dicing of customer data, including demographics, preferences, interactions, etc. can further help in customizing content with higher chances of consumption and engagement. Customer segmentation powered by CRM API data can help create content that customers resonate with.
CRM integration provides the marketing automation tool with every tiny detail of every lead to adjust and customize communication and campaigns that facilitate better nurturing. At the same time, real time conversation updates from CRM can help in timely marketing follow-ups for better chances of closure.
As customer data from CRM and marketing automation tools is synched in real time, any early signs of churn like reduced engagement or changed consumer behavior can be captured.
Real time alerts can also be automatically updated in the CRM for sales action. At the same time, marketing automation tools can leverage CRM data to predict which customers are more likely to churn and create specific campaigns to facilitate retention.
Users can leverage customer preferences from the CRM data to design campaigns with specific recommendations and even identify opportunities for upselling and cross-selling.
For instance, customers with high engagement might be interested in upgrading their relationships and the marketing automation tools can use this information and CRM details on their historical trends to propose best options for upselling.
Similarly, when details of customer transactions are captured in the CRM, they can be used to identify opportunities for complementary selling with dedicated campaigns. This leads to a clear increased revenue line.
In most marketing campaigns as the status of a lead changes, a new set of communication and campaign takes over. With CRM API integration, marketing automation tools can easily automate the campaign workflow in real time as soon as there is a status change in the CRM. This ensures greater engagement with the lead when their status changes.
Marketing communication after events is an extremely important aspect of sales. With CRM integration in marketing automation tools, automated post-event communication or campaigns can be triggered based on lead status for attendance and participation in the event.
This facilitates a faster turnaround time for engaging the customers just after the event, without any delays due to manual follow ups.
The integration can help automatically map the source of the lead from different marketing activities like webinars, social media posts, newsletters, etc. in your CRM to understand where your target audience engagement is higher.
At the same time, it can facilitate tagging of leads to the right teams or personnels for follow ups and closures. With automated lead source tracking, users can track the ROI of different marketing activities.
With CRM API integration, users can get access to customer preference insights to define their social media campaigns and audience. At the same time, they can customize scheduling based on customer’s geographical locations from CRM to facilitate maximum efficiency.
With bi-directional sync, CRM API integration with marketing automation tools can lead to enhancement of lead profiles. With more and more lead data coming in across both the platforms, users can have a rich and comprehensive profile of their customers, updates in real time across the CRM and marketing tools.
Overall, integrating CRM API with marketing automation tools can help in automating the entire marketing lifecycle. It starts with getting a full customer view to stage-based automated marketing campaigns to personalized nurturing and lead scoring, predictive analytics and much more. Most of the aspects of marketing based on the sales journey of the customer can be automated and triggered in real time with CRM changes.
Data insights from CRM API integrated with those from marketing automation tools can greatly help in creating reports to analyze and track customer behavior.
It can help ensure to understand consumer trends, identify the top marketing channels, improve customer segmentation and overall enhance the marketing strategy for more engagement.
While the benefits of CRM API integration with marketing automation tools are many, there are also some roadblocks on the way. Since each CRM API is different and your customers might be using different CRM systems, building and maintaining a plethora of CRM APIs can be challenging due to:
When data is exchanged between two applications, it needs to undergo transformation to become normalized with data fields compatible across both. Since each CRM API has diverse data models, syntax and nuances, inconsistency during data transfer is a big challenge.
If the data is not correctly normalized or transformed, chances are it might get corrupt or lost, leading to gaps in integration. At the same time, any inconsistency in data transformation and sync might lead to sending incorrect campaigns and triggers to customers, compromising on the experience.
While inconsistency in data transformation is one challenge, a related concern comes in the form of delays or limited real-time sync capabilities.
If the data sync between the CRM and the marketing automation tool is not happening in real time (across all CRMs being used), chances are that communication with end customers is being delayed, which can lead to loss of interest and lower engagement.
Any CRM is the beacon of sensitive customer data, often governed by GDPR and other compliances. However, integration and data transfer is always vulnerable to security threats like man in the middle attacks, DDoS, etc. which can lead to compromised privacy. This can lead to monetary and reputational risks.
With the increasing number of CRM applications, scalability of integration becomes a huge challenge. Building new CRM integrations can be very time and resource consuming — building one integration from scratch can take up to 3 months or more — which either means compromising on the available CRM integrations or choking of engineering bandwidth.
Moreover, as integrated CRM systems increase, the requirements for API calls and data exchange also grow exponentially, leading to delays in data sync and real time updates with increased data load. Invariably, scalability becomes a challenge.
Managing and maintaining integrations is a big challenge in itself. When end customers are using integrations, there are likely to be issues that require immediate action.
At the same time, maintaining detailed logs, tracking API calls, API syncs manually can be very tedious. However, any lag in this can crumble the entire integration system.
Finally, when integrating with different CRM APIs, managing the CRM vendors is a big challenge. Understanding API updates, managing different endpoints, ensuring zero downtime, error handling and coordinating with individual response teams is highly operational and time consuming.
Don’t let the CRM API integration challenges prevent you from leveraging the multiple benefits mentioned above. A unified CRM API like the one offered by Knit, can help you access the benefits without breaking sweat over the challenges.
If you want to know the technical details of how a unified API works, this will help
A unified CRM API facilitates integration with marketing automation tools within minutes, not months, which is usually what it takes to build integrations.
At the same time, it enables connecting with various CRM applications in one go. When it comes to Knit, marketing automation tools have to simply embed Knit’s UI component in their frontend to get access to Knit’s full catalog of CRM applications.
A unified CRM API can address all data transformation and normalization challenges easily. For instance, with Knit, different data models, nuances and schemas across CRM applications are mapped into a single and unified data model, facilitating data normalization in real time.
At the same time, Knit allows users to map custom data fields to access non-standard data.
The right unified CRM API can help you sync data in real time, without any external polling requests.
Take Knit for example, its webhooks and events driven architecture periodically polls data from all CRM applications, normalizing them and making them ready for use by the marketing automation tool. The latter doesn’t have to worry about the engineering intensive tasks of polling data, managing API calls, rate limits, data normalization, etc.
Furthermore, this ensures that as soon as details about a customer are updated on the CRM, the associated campaigns or triggers are automatically set in motion for marketing success.
There can be multiple CRM updates within a few minutes and as data load increases, a unified CRM API ensures guaranteed data sync in real time. As with Knit, its in-built retry mechanisms facilitate resilience and ensure that the marketing automation tools don’t miss out on any CRM updates, even at scale, as each lead is important.
Moreover, as a user, you can set up sync frequency as per your convenience.
With a unified CRM API, you only need to integrate once. As mentioned above, once you embed the UI component, every time you need to use a new CRM application or a new CRM API is added to Knit’s catalog, you can access it automatically with sync capabilities, without spending any engineering capabilities from your team.
This ensures that you can scale in the most resource-lite and efficient manner, without diverting engineering productivity from your core product. From a data sync perspective as well, a unified CRM API ensures guaranteed scalability, irrespective of the data load.
One of the biggest concerns of security and vulnerability to cyberattacks can be easily addressed with a unified CRM API across multiple facts. Let’s take the security provisions of Knit for example.
Finally, integration management to ensure that all your CRM APIs are healthy is well taken care of by a unified CRM API.
Finally, when you are using a unified API, you don’t have to deal with multiple vendors, endpoints, etc. Rather, the heavy lifting is done by the unified CRM API provider.
For instance, with Knit, you can access 24/7 support to securely manage your integrations. It also provides detailed documentation, links and easy to understand product walkthroughs for your developers and end users to ensure a smooth integration process.
If you are looking to integrate multiple CRM APIs with your product, get your Knit API keys and see unified API in action. (Getting started with Knit is completely free)
You can also talk to one of our experts to see how you can customize Knit to solve your specific integration challenges.
Developer resources on APIs and integrations
In the world of APIs, it's not enough to implement security measures and then sit back, hoping everything stays safe. The digital landscape is dynamic, and threats are ever-evolving.
Real-time monitoring provides an extra layer of protection by actively watching API traffic for any anomalies or suspicious patterns.
For instance -
In both cases, real-time monitoring can trigger alerts or automated responses, helping you take immediate action to safeguard your API and data.
Now, on similar lines, imagine having a detailed diary of every interaction and event within your home, from visitors to when and how they entered. Logging mechanisms in API security serve a similar purpose - they provide a detailed record of API activities, serving as a digital trail of events.
Logging is not just about compliance; it's about visibility and accountability. By implementing logging, you create a historical archive of who accessed your API, what they did, and when they did it. This not only helps you trace back and investigate incidents but also aids in understanding usage patterns and identifying potential vulnerabilities.
To ensure robust API security, your logging mechanisms should capture a wide range of information, including request and response data, user identities, IP addresses, timestamps, and error messages. This data can be invaluable for forensic analysis and incident response.
Combining logging with real-time monitoring amplifies your security posture. When unusual or suspicious activities are detected in real-time, the corresponding log entries provide context and a historical perspective, making it easier to determine the extent and impact of a security breach.
Based on factors like performance monitoring, security, scalability, ease of use, and budget constraints, you can choose a suitable API monitoring and logging tool for your application.
This is exactly what Knit does. Along with allowing you access to data from 50+ APIs with a single unified API, it also completely takes care of API logging and monitoring.
It offers a detailed Logs and Issues page that gives you a one page historical overview of all your webhooks and integrated accounts. It includes a number of API calls and provides necessary filters to choose your criterion. This helps you to always stay on top of user data and effectively manage your APIs.
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If you are looking to unlock 40+ HRIS and ATS integrations with a single API key, check out Knit API. If not, keep reading
Note: This is our master guide on API Pagination where we solve common developer queries in detail with common examples and code snippets. Feel free to visit the smaller guides linked later in this article on topics such as page size, error handling, pagination stability, caching strategies and more.
In the modern application development and data integration world, APIs (Application Programming Interfaces) serve as the backbone for connecting various systems and enabling seamless data exchange.
However, when working with APIs that return large datasets, efficient data retrieval becomes crucial for optimal performance and a smooth user experience. This is where API pagination comes into play.
In this article, we will discuss the best practices for implementing API pagination, ensuring that developers can handle large datasets effectively and deliver data in a manageable and efficient manner. (We have linked bite sized how-to guides on all API pagination FAQs you can think of in this article. Keep reading!)
But before we jump into the best practices, let’s go over what is API pagination and the standard pagination techniques used in the present day.
API pagination refers to a technique used in API design and development to retrieve large data sets in a structured and manageable manner. When an API endpoint returns a large amount of data, pagination allows the data to be divided into smaller, more manageable chunks or pages.
Each page contains a limited number of records or entries. The API consumer or client can then request subsequent pages to retrieve additional data until the entire dataset has been retrieved.
Pagination typically involves the use of parameters, such as offset and limit or cursor-based tokens, to control the size and position of the data subset to be retrieved.
These parameters determine the starting point and the number of records to include on each page.
By implementing API pagination, developers as well as consumers can have the following advantages -
Retrieving and processing smaller chunks of data reduces the response time and improves the overall efficiency of API calls. It minimizes the load on servers, network bandwidth, and client-side applications.
Since pagination retrieves data in smaller subsets, it reduces the amount of memory, processing power, and bandwidth required on both the server and the client side. This efficient resource utilization can lead to cost savings and improved scalability.
Paginated APIs provide a better user experience by delivering data in manageable portions. Users can navigate through the data incrementally, accessing specific pages or requesting more data as needed. This approach enables smoother interactions, faster rendering of results, and easier navigation through large datasets.
With pagination, only the necessary data is transferred over the network, reducing the amount of data transferred and improving network efficiency.
Pagination allows APIs to handle large datasets without overwhelming system resources. It provides a scalable solution for working with ever-growing data volumes and enables efficient data retrieval across different use cases and devices.
With pagination, error handling becomes more manageable. If an error occurs during data retrieval, only the affected page needs to be reloaded or processed, rather than reloading the entire dataset. This helps isolate and address errors more effectively, ensuring smoother error recovery and system stability.
Some of the most common, practical examples of API pagination are:
There are several common API pagination techniques that developers employ to implement efficient data retrieval. Here are a few useful ones you must know:
Read: Common API Pagination Techniques to learn more about each technique
When implementing API pagination in Python, there are several best practices to follow. For example,
Adopt a consistent naming convention for pagination parameters, such as "offset" and "limit" or "page" and "size." This makes it easier for API consumers to understand and use your pagination system.
Provide metadata in the API responses to convey additional information about the pagination.
This can include the total number of records, the current page, the number of pages, and links to the next and previous pages. This metadata helps API consumers navigate through the paginated data more effectively.
For example, here’s how the response of a paginated API should look like -
Select an optimal page size that balances the amount of data returned per page.
A smaller page size reduces the response payload and improves performance, while a larger page size reduces the number of requests required.
Determining an appropriate page size for a paginated API involves considering various factors, such as the nature of the data, performance considerations, and user experience.
Here are some guidelines to help you determine the optimal page size.
Read: How to determine the appropriate page size for a paginated API
Provide sorting and filtering parameters to allow API consumers to specify the order and subset of data they require. This enhances flexibility and enables users to retrieve targeted results efficiently. Here's an example of how you can implement sorting and filtering options in a paginated API using Python:
Ensure that the pagination remains stable and consistent between requests. Newly added or deleted records should not affect the order or positioning of existing records during pagination. This ensures that users can navigate through the data without encountering unexpected changes.
Read: 5 ways to preserve API pagination stability
Account for edge cases such as reaching the end of the dataset, handling invalid or out-of-range page requests, and gracefully handling errors.
Provide informative error messages and proper HTTP status codes to guide API consumers in handling pagination-related issues.
Read: 7 ways to handle common errors and invalid requests in API pagination
Implement caching mechanisms to store paginated data or metadata that does not frequently change.
Caching can help improve performance by reducing the load on the server and reducing the response time for subsequent requests.
Here are some caching strategies you can consider:
Cache the entire paginated response for each page. This means caching the data along with the pagination metadata. This strategy is suitable when the data is relatively static and doesn't change frequently.
Cache the result set of a specific query or combination of query parameters. This is useful when the same query parameters are frequently used, and the result set remains relatively stable for a certain period. You can cache the result set and serve it directly for subsequent requests with the same parameters.
Set an expiration time for the cache based on the expected freshness of the data. For example, cache the paginated response for a certain duration, such as 5 minutes or 1 hour. Subsequent requests within the cache duration can be served directly from the cache without hitting the server.
Use conditional caching mechanisms like HTTP ETag or Last-Modified headers. The server can respond with a 304 Not Modified status if the client's cached version is still valid. This reduces bandwidth consumption and improves response time when the data has not changed.
Implement a reverse proxy server like Nginx or Varnish in front of your API server to handle caching.
Reverse proxies can cache the API responses and serve them directly without forwarding the request to the backend API server.
This offloads the caching responsibility from the application server and improves performance.
In conclusion, implementing effective API pagination is essential for providing efficient and user-friendly access to large datasets. But it isn’t easy, especially when you are dealing with a large number of API integrations.
Using a unified API solution like Knit ensures that your API pagination requirements is handled without you requiring to do anything anything other than embedding Knit’s UI component on your end.
Once you have integrated with Knit for a specific software category such as HRIS, ATS or CRM, it automatically connects you with all the APIs within that category and ensures that you are ready to sync data with your desired app.
In this process, Knit also fully takes care of API authorization, authentication, pagination, rate limiting and day-to-day maintenance of the integrations so that you can focus on what’s truly important to you i.e. building your core product.
By incorporating these best practices into the design and implementation of paginated APIs, Knit creates highly performant, scalable, and user-friendly interfaces for accessing large datasets. This further helps you to empower your end users to efficiently navigate and retrieve the data they need, ultimately enhancing the overall API experience.
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Note: This is a part of our series on API Pagination where we solve common developer queries in detail with common examples and code snippets. Please read the full guide here where we discuss page size, error handling, pagination stability, caching strategies and more.
Ensure that the pagination remains stable and consistent between requests. Newly added or deleted records should not affect the order or positioning of existing records during pagination. This ensures that users can navigate through the data without encountering unexpected changes.
To ensure that API pagination remains stable and consistent between requests, follow these guidelines:
If you're implementing sorting in your pagination, ensure that the sorting mechanism remains stable.
This means that when multiple records have the same value for the sorting field, their relative order should not change between requests.
For example, if you sort by the "date" field, make sure that records with the same date always appear in the same order.
Avoid making any changes to the order or positioning of records during pagination, unless explicitly requested by the API consumer.
If new records are added or existing records are modified, they should not disrupt the pagination order or cause existing records to shift unexpectedly.
It's good practice to use unique and immutable identifiers for the records being paginated. T
This ensures that even if the data changes, the identifiers remain constant, allowing consistent pagination. It can be a primary key or a unique identifier associated with each record.
If a record is deleted between paginated requests, it should not affect the pagination order or cause missing records.
Ensure that the deletion of a record does not leave a gap in the pagination sequence.
For example, if record X is deleted, subsequent requests should not suddenly skip to record Y without any explanation.
Employ pagination techniques that offer deterministic results. Techniques like cursor-based pagination or keyset pagination, where the pagination is based on specific attributes like timestamps or unique identifiers, provide stability and consistency between requests.
Also Read: 5 caching strategies to improve API pagination performance
Deep dives into the Knit product and APIs
HRIS or Human Resources Information Systems have become commonplace for organizations to simplify the way they manage and use employee information. For most organizations, information stored and updated in the HRIS becomes the backbone for provisioning other applications and systems in use. HRIS enables companies to seamlessly onboard employees, set them up for success and even manage their payroll and other functions to create an exemplary employee experience.
However, integration of HRIS APIs with other applications under use is essential to facilitate workflow automation. Essentially, HRIS API integration can help businesses connect diverse applications with the HRIS to ensure seamless flow of information between the connected applications. HRIS API integrations can either be internal or customer-facing. In internal HRIS integrations, businesses connect their HRIS with other applications they use, like ATS, Payroll, etc. to automate the flow of information between the same. On the other hand, with customer-facing HRIS integrations, businesses can connect their application or product with the end customer’s HR applications for data exchange.
This article seeks to serve as a comprehensive repository on HRIS API integration, covering the benefits, best practices, challenges and how to address them, use cases, data models, troubleshooting and security risks, among others.
Here are some of the top reasons why businesses need HRIS API integration, highlighting the benefits they bring along:
The different HRIS tools you use are bound to come with different data models or fields which will capture data for exchange between applications. It is important for HR professionals and those building and managing these integrations to understand these data models, especially to ensure normalization and transformation of data when it moves from one application to another.
This includes details of all employees whether full time or contractual, including first and last name, contact details, date of birth, email ID, etc. At the same time, it covers other details on demographics and employment history including status, start date, marital status, gender, etc. In case of a former employee, this field also captures termination date.
This includes personal details of the employee, including personal phone number, address, etc. which can be used to contact employees beyond work contact information.
Employee profile picture object or data model captures the profile picture of the employees that can be used across employee records and purposes.
The next data model in discussion focuses on the type or the nature of employment. An organization can hire full time employees, contractual workers, gig workers, volunteers, etc. This distinction in employment type helps differentiate between payroll specifications, taxation rules, benefits, etc.
Location object or data model refers to the geographical area for the employee. Here, both the work location as well as the residential or native/ home location of the employee is captured. This field captures address, country, zip code, etc.
Leave request data model focuses on capturing all the time off or leave of absence entries made by the employee. It includes detailing the nature of leave, time period, status, reason, etc.
Each employee, based on their nature of employment, is entitled to certain time off in a year. The leave balance object helps organizations keep a track of the remaining balance of leave of absence left with the employee. With this, organizations can ensure accurate payroll, benefits and compensation.
This data model captures the attendance of employees, including fields like time in, time out, number of working hours, shift timing, status, break time, etc.
Each organization has a hierarchical structure or layers which depict an employee’s position in the whole scheme of things. The organizational structure object helps understand an employee’s designation, department, manager (s), direct reportees, etc.
This data model focuses on capturing the bank details of the employee, along with other financial details like a linked account for transfer of salary and other benefits that the employee is entitled to. In addition, it captures routing information like Swift Code, IFSC Code, Branch Code, etc.
Dependents object focuses on the family members of an employee or individuals who the employee has confirmed as dependents for purposes of insurance, family details, etc. This also includes details of employees’ dependents including their date of birth, relation to the employee, among others.
This includes the background verification and other details about an employee with some identification proof and KYC (know your customer) documents. This is essential for companies to ensure their employees are well meaning citizens of the country meeting all compliances to work in that location. It captures details like Aadhar Number, PAN Number or unique identification number for the KYC document.
This data model captures all details related to compensation for an employee, including total compensation/ cost to company, compensation split, salary in hand, etc. It also includes details on fixed compensation, variable pay as well as stock options. Compensation object also captures the frequency of salary payment, pay period, etc.
To help you leverage the benefits of HRIS API integrations, here are a few best practices that developers and teams that are managing integrations can adopt:
This is extremely important if you are building integrations in-house or wish to connect with HRIS APIs in a 1:1 model. Building each HRIS integration or connecting with each HR application in-house can take four weeks on an average, with an associated cost of ~$10K. Therefore, it is essential to prioritize which HRIS integrations are pivotal for the short term versus which ones can be pushed to a later period. If developers focus all their energy in building all HRIS integrations at once, it may lead to delays in other product features.
Developers should spend sufficient time in researching and understanding each individual HRIS API they are integrating with, especially in a 1:1 case. For instance, REST vs SOAP APIs have different protocols and thus, must be navigated in different ways. Similarly, the API data model, URL and the way the HRIS API receives and sends data will be distinct across each application. Developers must understand the different URLs and API endpoints for staging and live environments, identify how the HRIS API reports errors and how to respond to them, the supported data formats (JSON/ XML), etc.
As HRIS vendors add new features, functionalities and update the applications, the APIs keep changing. Thus, as a best practice, developers must support API versioning to ensure that any changes can be updated without impacting the integration workflow and compatibility. To ensure conducive API versioning, developers must regularly update to the latest version of the API to prevent any disruption when the old version is removed. Furthermore, developers should eliminate the reliance on or usage of deprecated features, endpoints or parameters and facilitate the use of fallbacks or system alter notifications for unprecedented changes.
When building and managing integrations in-house, developers must be conscious and cautious about rate limiting. Overstepping the rate limit can prevent API access, leading to integration workflow disruption. To facilitate this, developers should collaboratively work with the API provider to set realistic rate limits based on the actual usage. At the same time, it is important to constantly review rate limits against the usage and preemptively upgrade the same in case of anticipated exhaustion. Also, developers should consider scenarios and brainstorm with those who use the integration processes the maximum to identify ways to optimize API usage.
Documenting the integration process for each HRIS is extremely important. It ensures there is a clear record of everything about that integration in case a developer leaves the organization, fostering integration continuity and seamless error handling. Furthermore, it enhances the long-term maintainability of the HRIS API integration. A comprehensive document generally captures the needs and objectives of the integration, authentication methods, rate limits, API types and protocols, testing environments, safety net in case the API is discontinued, common troubleshooting errors and handling procedures, etc. At the same time this documentation should be stored in a centralized repository which is easily accessible.
HRIS integration is only complete once it is tested across different settings and they continue to deliver consistent performance. Testing is also an ongoing process, because everytime there is an update in the API of the third-party application, testing is needed, and so is the case whenever there is an update in one’s own application. To facilitate robust testing, automation is the key. Additionally, developers can set up test pipelines and focus on monitoring and logging of issues. It is also important to check for backward compatibility, evaluate error handling implementation and boundary values and keep the tests updated.
Each HRIS API in the market will have distinct documentation highlighting its endpoints, authentication methods, etc. To make HRIS API integration for developers simpler, we have created a repository of different HR application directories, detailing how to navigate integrations with them:
While there are several benefits of HRIS API integration, the process is fraught with obstacles and challenges, including:
Today, there are 1000s of HR applications in the market which organizations use. This leads to a huge diversity of HRIS API providers. Within the HRIS category, the API endpoints, type of API (REST vs SOAP), data models, syntax, authentication measures and standards, etc. can vary significantly. This poses a significant challenge for developers who have to individually study and understand each HRIS API before integration. At the same time, the diversity also contributes to making the integration process time consuming and resource intensive.
The next challenge comes from the fact that not all HRIS APIs are publicly available. This means that these gated APIs require organizations to get into partnership agreements with them in order to access API key, documentation and other resources. Furthermore, the process of partnering is not always straightforward either. It ranges from background and security checks to lengthy negotiations, and at times come at a premium cost associated. At the same time, even when APIs are public, their documentation is often poor, incomplete and difficult to understand, adding another layer of complexity to building and maintaining HRIS API integrations.
As mentioned in one of the sections above, testing is an integral part of HRIS API integration. However, it poses a significant challenge for many developers. On the one hand, not every API provider offers testing environments to build against, pushing developers to use real customer data. On the other hand, even if the testing environment is available, running integrations against the same, requires thorough understanding and a steep learning curve for SaaS product developers. Overall, testing becomes a major roadblock, slowing down the process of building and maintaining integrations.
When it comes to HRIS API integration, there are several data related challenges that developers face across the way. To begin with, different HR providers are likely to share the same information in different formats, fields and names. Furthermore, data may also not come in a simple format, forcing developers to collect and calculate the data to decipher some values out of it. Data quality adds another layer of challenges. SInce standardizing and transforming data into a unified format is difficult, ensuring its accuracy, timeliness, and consistency is a big obstacle for developers.
Scaling HRIS API integrations can be a daunting task, especially when integrations have to be built 1:1, in-house. Since building each integration requires developers to understand the API documentation, decipher data complexities, create custom codes and manage authentication, the process is difficult to scale. While building a couple of integrations for internal use might be feasible, scaling customer-facing integrations leads to a high level of inefficient resource use and developer fatigue.
Keeping up with third-party APIs and integration maintenance is another challenge that developers face. To begin with as the API versions update and change, HRIS API integration must reflect those changes to ensure usability and compatibility. However API documentation seldom reflects these changes, making it a cumbersome task for developers to keep pace with the changes. And, the inability to update API versioning can lead to broken integrations, endpoints and consistency issues. Furthermore, monitoring and logging, necessary to monitor the health of integrations can be a big challenge, with an additional resource allocation towards checking logs and addressing errors promptly. Managing rate limiting and throttling are some of the other post integration maintenance challenges that developers tend to face.
Knit provides a unified HRIS API that streamlines the integration of HRIS solutions. Instead of connecting directly with multiple HRIS APIs, Knit allows you to connect with top providers like Workday, Successfactors, BambooHr, and many others through a single integration.
Learn more about the benefits of using a unified API.
Getting started with Knit is simple. In just 5 steps, you can embed multiple HRIS integrations into your APP.
Steps Overview:
For detailed integration steps with the unified HRIS APIt, visit:
Security happens to be one of the main tenets of HRIS API integration, determining its success and effectiveness. As HRIS API integration facilitates transmission, exchange and storage of sensitive employee data and related information, security is of utmost importance.
HRIS API endpoints are highly vulnerable to unauthorized access attempts. The lack of robust security protocols, these vulnerabilities can be exploited and attackers can gain access to sensitive HR information. On the one hand, this can lead to data breaches and public exposure of confidential employee data. On the other hand, it can disrupt the existing systems and create havoc. Here are the top security considerations and best practices to keep in mind for HRIS API integration.
Authentication is the first step to ensure HRIS API security. It seeks to verify or validate the identity of a user who is trying to gain access to an API, and ensures that the one requesting the access is who they claim to be. The top authentication protocols include:
Most authentication methods rely on API tokens. However, when they are not securely generated, stored, or transmitted, they become vulnerable to attacks. Broken authentication can grant access to attackers, which can cause session hijacking, giving the attackers complete control over the API session. Hence, securing API tokens and authentication protocols is imperative. Practices like limiting the lifespan of your tokens/API keys, via time-based or event-based expiration as well as securing credentials in secret vault services can.
As mentioned, HRIS API integration involves transmission and exchange of sensitive and confidential employee information. However, if the data is not encrypted during transmission it is vulnerable to attacker interception. This can happen when APIs use insecure protocols (HTTP instead of HTTPS), data is transmitted as plain text without encryption, there is insufficient data masking and validation.
To facilitate secure data transmission, it is important to use HTTPS, which uses Transport Layer Security (TLS) or its predecessor, Secure Sockets Layer (SSL), to encrypt data and can only be decrypted when it reaches the intended recipient.
Input validation failures can increase the incidence of injection attacks in HRIS API integrations. These attacks, primarily SQL injection and cross-site scripting (XSS), manipulate input data or untrusted data is injected into the database queries. This enables attackers to execute unauthorized database operations, potentially accessing or modifying sensitive information.
Practices like input validation, output encoding, and the principle of least privilege, can help safeguard against injection vulnerabilities. Similarly, for database queries, using parameterized statements instead of injecting user inputs directly into SQL queries, can help mitigate the threat.
HRIS APIs are extremely vulnerable to denial of service (DoS) attacks where attackers flood your systems with excessive requests which it is not able to process, leading to disruption and temporarily restricts its functionality. Human errors, misconfigurations or even compromised third party applications can lead to this particular security challenge.
Rate limiting and throttling are effective measures that help prevent the incidence of DoS attacks, protecting APIs against excessive or abusive use and facilitating equitable request distribution between customers. While rate limiting restricts the number of requests or API calls that can be made in a specified time period, throttling slows down the processing of requests, instead of restricting them. Together, these act as robust measures to prevent excessive use attacks by perpetrators, and even protects against brute-force attacks.
Third party security concerns i.e. how secure or vulnerable the third-party applications which you are integrating with, have a direct impact on the security posture of your HRIS API integration. Furthermore, threats and vulnerabilities come in without any prompt, making them unwanted guests.
To address the security concerns of third-party applications, it is important to thoroughly review the credibility and security posture of the software you integrate with. Furthermore, be cautious of the level of access you grant, sticking to the minimum requirement. It is equally important to monitor security updates and patch management along with a prepared contingency plan to mitigate the risk of security breaches and downtime in case the third-party application suffers a breach.
Furthermore, API monitoring and logging are critical security considerations for HRIS API integration. While monitoring involves continuous tracking of API traffic, logging entails maintaining detailed historical records of all API interactions. Together they are invaluable for troubleshooting, debugging, fostering trigger alerts in case security thresholds have been breached. In addition, regular security audits and penetration testing are extremely important. While security audits ensure the review of an API's design, architecture, and implementation to identify security weaknesses, misconfigurations, and best practice violations, penetration testing simulates cyberattacks to identify vulnerabilities, weaknesses, and potential entry points that malicious actors could exploit. These practices help mitigate ongoing security threats and facilitate API trustworthiness.
When dealing with a large number of HRIS API integrations, security considerations and challenges increase exponentially. In such a situation, a unified API like Knit can help address all concerns effectively. Knit’s HRIS API ensures safe and high quality data access by:
Here’s a quick snapshot of how HRIS integration can be used across different scenarios.
ATS or applicant tracking system can leverage HRIS integration to ensure that all important and relevant details about new employees, including name, contact information, demographic and educational backgrounds, etc. are automatically updated into the customer’s preferred HRIS tool without the need to manually entering data, which can lead to inaccuracies and is operationally taxing. ATS tools leverage the write HRIS API and provide data to the HR tools in use.
Examples: Greenhouse Software, Workable, BambooHR, Lever, Zoho
Payroll software plays an integral role in any company’s HR processes. It focuses on ensuring that everything related to payroll and compensation for employees is accurate and up to date. HRIS integration with payroll software enables the latter to get automated and real time access to employee data including time off, work schedule, shifts undertaken, payments made on behalf of the company, etc.
At the same time, it gets access to employee data on bank details, tax slabs, etc. Together, this enables the payroll software to deliver accurate payslips to its customers, regarding the latter’s employees. With automated integration, data sync can be prone to errors, which can lead to faulty compensation disbursal and many compliance challenges. HRIS integration, when done right, can alert the payroll software with any new addition to the employee database in real time to ensure setting up of their payroll immediately. At the same time, once payslips are made and salaries are disbursed, payroll software can leverage HRIS integration to write back this data into the HR software for records.
Examples: Gusto, RUN Powered by ADP, Paylocity, Rippling
Employee onboarding software uses HRIS integration to ensure a smooth onboarding process, free of administrative challenges. Onboarding tools leverage the read HRIS APIs to get access to all the data for new employees to set up their accounts across different platforms, set up payroll, get access to bank details, benefits, etc.
With HRIS integrations, employee onboarding software can provide their clients with automated onboarding support without the need to manually retrieve data for each new joiner to set up their systems and accounts. Furthermore, HRIS integration also ensures that when an employee leaves an organization, the update is automatically communicated to the onboarding software to push deprovisioning of the systems, and services. This also ensures that access to any tools, files, or any other confidential access is terminated. Manually deprovisioning access can lead to some manual errors, and even cause delays in exit formalities.
Examples: Deel, Savvy, Sappling
With the right HRIS integration, HR teams can integrate all relevant data and send out communication and key announcements in a centralized manner. HRIS integrations ensure that the announcements reach all employees on the correct contact information without the need for HR teams to individually communicate the needful.
LMS tools leverage both the read and write HRIS APIs. On the one hand, they read or get access to all relevant employee data including roles, organizational structure, skills demand, competencies, etc. from the HRIS tool being used. Based on this data, they curate personalized learning and training modules for employees for effective upskilling. Once the training is administered, the LMS tools again leverage HRIS integrations to write data back into the HRIS platform with the status of the training, including whether or not the employee has completed the same, how did they perform, updating new certifications, etc. Such integration ensures that all learning modules align well with employee data and profiles, as well as all training are captured to enhance the employee’s portfolio.
Example: TalentLMS, 360Learning, Docebo, Google Classroom
Similar to LMS, workforce management and scheduling tools utilize both read and write HRIS APIs. The consolidated data and employee profile, detailing their competencies and training undertaken can help workforce management tools suggest the best delegation of work for companies, leading to resource optimization. On the other hand, scheduling tools can feed data automatically with HRIS integration into HR tools about the number of hours employees have worked, their time off, free bandwidth for allocation, shift schedules etc. HRIS integration can help easily sync employee work schedules and roster data to get a clear picture of each employee’s schedule and contribution.
Examples: QuickBooks Time, When I Work
HRIS integration for benefits administration tools ensures that employees are provided with the benefits accurately, customized to their contribution and set parameters in the organization. Benefits administration tools can automatically connect with the employee data and records of their customers to understand the benefits they are eligible for based on the organizational structure, employment type, etc. They can read employee data to determine the benefits that employees are entitled to. Furthermore, based on employee data, they feed relevant information back into the HR software, which can further be leveraged by payroll software used by the customers to ensure accurate payslip creation.
Examples: TriNet Zenefits, Rippling, PeopleKeep, Ceridian Dayforce
Workforce planning tools essentially help companies identify the gap in their talent pipeline to create strategic recruitment plans. They help understand the current capabilities to determine future hiring needs. HRIS integration with such tools can help automatically sync the current employee data, with a focus on organizational structure, key competencies, training offered, etc. Such insights can help workforce planning tools accurately manage talent demands for any organization. At the same time, real time sync with data from HR tools ensures that workforce planning can be updated in real time.
There are several reasons why HRIS API integrations fail, highlighting that there can be a variety of errors. Invariably, teams need to be equipped to efficiently handle any integration errors, ensuring error resolution in a timely manner, with minimal downtime. Here are a few points to facilitate effective HRIS API integration error handling.
Start with understanding the types of errors or response codes that come in return of an API call. Some of the common error codes include:
While these are some, there are other error codes which are common in nature and, thus, proactive resolution should be available.
All errors are generally captured in the monitoring system the business uses for tracking issues. For effective HRIS API error handling, it is imperative that the monitoring system be configured in such a way that it not only captures the error code but also any other relevant details that may be displayed along with it. These can include a longer descriptive message detailing the error, a timestamp, suggestion to address the error, etc. Capturing these can help developers with troubleshooting the challenge and resolve the issues faster.
This error handling technique is specifically beneficial for rate limit errors or whenever you exceed your request quota. Exponential backoffs allow users to retry specific API calls at an increasing interval to retrieve any missed information. The request may be retrieved in the subsequent window. This is helpful as it gives the system time to recover and reduces the number of failed requests due to rate limits and even saves the costs associated with these unnecessary API calls.
It is very important to test the error handling processes by running sandbox experiments and simulated environment testing. Ideally, all potential errors should be tested for, to ensure maximum efficiency. However, in case of time and resource constraints, the common errors mentioned above, including HTTP status code errors, like 404 Not Found, 401 Unauthorized, and 503 Service Unavailable, must be tested for.
In addition to robust testing, every step of the error handling process must be documented. Documentation ensures that even in case of engineering turnover, your HRIS API integrations are not left to be poorly maintained with new teams unable to handle errors or taking longer than needed. At the same time, having comprehensive error handling documentation can make any knowledge transfer to new developers faster. Ensure that the documentation not only lists the common errors, but also details each step to address the issues with case studies and provides a contingency plan for immediate business continuity.
Furthermore, reviewing and refining the error handling process is imperative. As APIs undergo changes, it is normal for initial error handling processes to fail and not perform as expected. Therefore, error handling processes must be consistently reviewed and upgraded to ensure relevance and performance.
Knit’s HRIS API simplifies the error handling process to a great extent. As a unified API, it helps businesses automatically detect and resolve HRIS API integration issues or provide the customer-facing teams with quick resolutions. Businesses do not have to allocate resources and time to identify issues and then figure out remedial steps. For instance, Knit’s retry and delay mechanisms take care of any API errors arising due to rate limits.
It is evident that HRIS API integration is no longer a good to have, but an imperative for businesses to manage all employee related operations. Be it integrating HRIS and other applications internally or offering customer facing integrations, there are several benefits that HRIS API integration brings along, ranging from reduced human error to greater productivity, customer satisfaction, etc. When it comes to offering customer-facing integrations, ATS, payroll, employee onboarding/ offboarding, LMS tools are a few among the many providers that see value with real world use cases.
However, HRIS API integration is fraught with challenges due to the diversity of HR providers and the different protocols, syntax, authentication models, etc. they use. Scalining integrations, testing across different environments, security considerations, data normalization, all create multidimensional challenges for businesses. Invariably, businesses are now going the unified API way to build and manage their HRIS API integration. Knit’s unified HRIS API ensures:
Knit’s HRIS API ensures a high ROI for companies with a single type of authentication, pagination, rate limiting, and automated issue detection making the HRIS API integration process simple.
Finch is a leading unified API player, particularly popular for its connectors in the employment systems space, enabling SaaS companies to build 1: many integrations with applications specific to employment operations. This translates to the ease for customers to easily leverage Finch’s unified connector to integrate with multiple applications in HRIS and payroll categories in one go. Invariably, owing to Finch, companies find connecting with their preferred employment applications (HRIS and payroll) seamless, cost-effective, time-efficient, and overall an optimized process. While Finch has the most exhaustive coverage for employment systems, it's not without its downsides - most prominent being the fact that a majority of the connectors offered are what Finch calls “assisted” integrations. Assisted essentially means a human-in-the-loop integration where a person has admin access to your user's data and is manually downloading and uploading the data as and when needed.
● Ability to scale HRIS and payroll integrations quickly
● In-depth data standardization and write-back capabilities
● Simplified onboarding experience within a few steps
● Most integrations are human-assisted instead of being true API integrations
● Integrations only available for employment systems
● Limited flexibility for frontend auth component
● Requires users to take the onus for integration management
Pricing: Starts at $35/connection per month for read only apis; Write APIs for employees, payroll and deductions are available on their scale plan for which you’d have to get in touch with their sales team.
Now let's look at a few alternatives you can consider alongside finch for scaling your integrations
Knit is a leading alternative to Finch, providing unified APIs across many integration categories, allowing companies to use a single connector to integrate with multiple applications. Here’s a list of features that make Knit a credible alternative to Finch to help you ship and scale your integration journey with its 1:many integration connector:
Pricing: Starts at $2400 Annually
● Wide horizontal and deep vertical coverage: Knit not only provides a deep vertical coverage within the application categories it supports, like Finch, however, it also supports a wider horizontal coverage of applications, higher than that of Finch. In addition to applications within the employment systems category, Knit also supports a unified API for ATS, CRM, e-Signature, Accounting, Communication and more. This means that users can leverage Knit to connect with a wider ecosystem of SaaS applications.
● Events-driven webhook architecture for data sync: Knit has built a 100% events-driven webhook architecture, which ensures data sync in real time. This cannot be accomplished using data sync approaches that require a polling infrastructure. Knit ensures that as soon as data updates happen, they are dispatched to the organization’s data servers, without the need to pull data periodically. In addition, Knit ensures guaranteed scalability and delivery, irrespective of the data load, offering a 99.99% SLA. Thus, it ensures security, scale and resilience for event driven stream processing, with near real time data delivery.
● Data security: Knit is the only unified API provider in the market today that doesn’t store any copy of the customer data at its end. This has been accomplished by ensuring that all data requests that come are pass through in nature, and are not stored in Knit’s servers. This extends security and privacy to the next level, since no data is stored in Knit’s servers, the data is not vulnerable to unauthorized access to any third party. This makes convincing customers about the security potential of the application easier and faster.
● Custom data models: While Knit provides a unified and standardized model for building and managing integrations, it comes with various customization capabilities as well. First, it supports custom data models. This ensures that users are able to map custom data fields, which may not be supported by unified data models. Users can access and map all data fields and manage them directly from the dashboard without writing a single line of code. These DIY dashboards for non-standard data fields can easily be managed by frontline CX teams and don’t require engineering expertise.
● Sync when needed: Knit allows users to limit data sync and API calls as per the need. Users can set filters to sync only targeted data which is needed, instead of syncing all updated data, saving network and storage costs. At the same time, they can control the sync frequency to start, pause or stop sync as per the need.
● Ongoing integration management: Knit’s integration dashboard provides comprehensive capabilities. In addition to offering RCA and resolution, Knit plays a proactive role in identifying and fixing integration issues before a customer can report it. Knit ensures complete visibility into the integration activity, including the ability to identify which records were synced, ability to rerun syncs etc.
● No-Human in the loop integrations
● No need for maintaining any additional polling infrastructure
● Real time data sync, irrespective of data load, with guaranteed scalability and delivery
● Complete visibility into integration activity and proactive issue identification and resolution
● No storage of customer data on Knit’s servers
● Custom data models, sync frequency, and auth component for greater flexibility
Another leading contender in the Finch alternative for API integration is Merge. One of the key reasons customers choose Merge over Finch is the diversity of integration categories it supports.
Pricing: Starts at $7800/ year and goes up to $55K
● Higher number of unified API categories; Merge supports 7 unified API categories, whereas Finch only offers integrations for employment systems
● Supports API-based integrations and doesn’t focus only on assisted integrations (as is the case for Finch), as the latter can compromise customer’s PII data
● Facilitates data sync at a higher frequency as compared to Finch; Merge ensures daily if not hourly syncs, whereas Finch can take as much as 2 weeks for data sync
● Requires a polling infrastructure that the user needs to manage for data syncs
● Limited flexibility in case of auth component to customize customer frontend to make it similar to the overall application experience
● Webhooks based data sync doesn’t guarantee scale and data delivery
Workato is considered another alternative to Finch, albeit in the traditional and embedded iPaaS category.
Pricing: Pricing is available on request based on workspace requirement; Demo and free trial available
● Supports 1200+ pre-built connectors, across CRM, HRIS, ticketing and machine learning models, facilitating companies to scale integrations extremely fast and in a resource efficient manner
● Helps build internal integrations, API endpoints and workflow applications, in addition to customer-facing integrations; co-pilot can help build workflow automation better
● Facilitates building interactive workflow automations with Slack, Microsoft Teams, with its customizable platform bot, Workbot
However, there are some points you should consider before going with Workato:
● Lacks an intuitive or robust tool to help identify, diagnose and resolve issues with customer-facing integrations themselves i.e., error tracing and remediation is difficult
● Doesn’t offer sandboxing for building and testing integrations
● Limited ability to handle large, complex enterprise integrations
Paragon is another embedded iPaaS that companies have been using to power their integrations as an alternative to Finch.
Pricing: Pricing is available on request based on workspace requirement;
● Significant reduction in production time and resources required for building integrations, leading to faster time to market
● Fully managed authentication, set under full sets of penetration and testing to secure customers’ data and credentials; managed on-premise deployment to support strictest security requirements
● Provides a fully white-labeled and native-modal UI, in-app integration catalog and headless SDK to support custom UI
However, a few points need to be paid attention to, before making a final choice for Paragon:
● Requires technical knowledge and engineering involvement to custom-code solutions or custom logic to catch and debug errors
● Requires building one integration at a time, and requires engineering to build each integration, reducing the pace of integration, hindering scalability
● Limited UI/UI customization capabilities
Tray.io provides integration and automation capabilities, in addition to being an embedded iPaaS to support API integration.
Pricing: Supports unlimited workflows and usage-based pricing across different tiers starting from 3 workspaces; pricing is based on the plan, usage and add-ons
● Supports multiple pre-built integrations and automation templates for different use cases
● Helps build and manage API endpoints and support internal integration use cases in addition to product integrations
● Provides Merlin AI which is an autonomous agent to build automations via chat interface, without the need to write code
However, Tray.io has a few limitations that users need to be aware of:
● Difficult to scale at speed as it requires building one integration at a time and even requires technical expertise
● Data normalization capabilities are rather limited, with additional resources needed for data mapping and transformation
● Limited backend visibility with no access to third-party sandboxes
We have talked about the different providers through which companies can build and ship API integrations, including, unified API, embedded iPaaS, etc. These are all credible alternatives to Finch with diverse strengths, suitable for different use cases. Undoubtedly, the number of integrations supported within employment systems by Finch is quite large, there are other gaps which these alternatives seek to bridge:
● Knit: Providing unified apis for different categories, supporting both read and write use cases. A great alternative which doesn’t require a polling infrastructure for data sync (as it has a 100% webhooks based architecture), and also supports in-depth integration management with the ability to rerun syncs and track when records were synced.
● Merge: Provides a greater coverage for different integration categories and supports data sync at a higher frequency than Finch, but still requires maintaining a polling infrastructure and limited auth customization.
● Workato: Supports a rich catalog of pre-built connectors and can also be used for building and maintaining internal integrations. However, it lacks intuitive error tracing and remediation.
● Paragon: Fully managed authentication and fully white labeled UI, but requires technical knowledge and engineering involvement to write custom codes.
● Tray.io: Supports multiple pre-built integrations and automation templates and even helps in building and managing API endpoints. But, requires building one integration at a time with limited data normalization capabilities.
Thus, consider the following while choosing a Finch alternative for your SaaS integrations:
● Support for both read and write use-cases
● Security both in terms of data storage and access to data to team members
● Pricing framework, i.e., if it supports usage-based, API call-based, user based, etc.
● Features needed and the speed and scope to scale (1:many and number of integrations supported)
Depending on your requirements, you can choose an alternative which offers a greater number of API categories, higher security measurements, data sync (almost in real time) and normalization, but with customization capabilities.
As hiring needs for organizations become more complex, assessing candidates in a holistic and comprehensive manner is more critical than ever. Fortunately, multiple assessment software have surfaced in the recent past, enabling organizations to carry out assessments in the most effective and efficient manner. Leveraging technology, gamification and other advances, such tools are able to help organizations ensure that a candidate is a perfect fit for the role, skills, company culture and all other parameters.
However, to make the best use of assessment software, it is important to integrate data and information from them across other platforms being used for operational efficiency and faster turnaround in recruitment and onboarding. Here, assessment API integration plays a major role.
When organizations integrate data from the assessment API with other applications, including ATS, HRIS, interview scheduling, etc., they are able to optimize their recruitment workflow with a high degree of automation.
In this article, we will discuss the different aspects of assessment API, its integration use cases, key data models and the different ways in which you can accomplish seamless integration.
To ensure that you understand the different assessment APIs well, it is important to comprehend the data models or fields that are commonly used. One of the major reasons that the knowledge of data models is imperative is to facilitate data transformation and normalization during data sync. Here are the common data models for assessment APIs:
This data model focuses on the name of the candidate to whom a particular assessment will be administered and all records pertaining to the candidate will be stored. It can also be associated with a unique candidate ID to prevent any confusion in case of duplication of names.
The next data model captures the profile of the candidate. From an assessment software perspective, the focus is on a candidate’s professional profile, prior work experience, qualifications, certifications, competencies, etc. Such details help in determining the right assessments for each candidate based on their experience and the role for which they are being assessed.
This data field keeps the details or contact information for all candidates, including phone number, email address, etc. The contact information ensures that the candidate’s can be easily informed about their assessment schedule, any changes in the schedule, results, status, etc. it facilitates smooth communication between the assessment software and the candidate.
Most assessment software capture candidate pictures to ensure authenticity during assessments or training. Candidate profile pictures in assessment software databases help the latter to prevent proxy attendance during interviews or assessments and address any potential foul play.
The next data model captures the nature of employment or the type of job. Today, in addition to full-time employees, organizations are increasingly hiring consultants, gig workers and even contractual employees. The assessment requirements for each one of them can be varied. Thus, the assessment software has a data model to capture the job type to ensure appropriate assessments.
Assessment API captures job information or job details as an important data model. Put simply, this model has all details about the role being assessed for, the requirements, skills, competencies, and other aspects which need to be assessed. As a data model or field, job information contains all aspects of the job that need to be matched when candidates are assessed.
Next in line is the data model which focuses on the job department and managers. This particular field captures the department for which the candidate has applied for and the hiring managers. The details of hiring managers are important because the results of the assessment tests have to be sent to them.
Most assessment software have a few stages that a candidate undergoes. It can start from a normal personality test and go on to psychometric evaluations, coding tests, to personal interviews. As a data model, assessment stages help hiring managers understand where the candidates stand in the hiring pipeline and how close or far they are from closing a particular role at hand.
The next data model captures all the types of assessments that are available as a part of the assessment software. This field has a repository of different assessments that can be administered.
Once the assessment is administered, an important data model is the scorecard. This captures how the candidate performed for a particular assessment. The scorecard format or type can be different and unique for each assessment type. In some, it can be an absolute and objective score, while some others might give a more subjective outcome, determining the suitability of the candidate for the role.
The assessment result as a data model captures the final verdict for the candidate. More often than not, hiring managers can update the result as selected, rejected or any other based on the scorecard and other evaluations undertaken, post which the data can be integrated into the next workflow software.
This data field or data model captures any attachments that come along with a particular assessment test. Some tests might require candidates to submit their assessments as an attachment or external document. This field contains all such attachments which can be consulted during final hiring decisions.
The assessment status data model captures the status of the assessment test for a particular candidate. It captures if the test has been provided to the candidate, whether or not they have completed the same, etc.
Now that there is a clear understanding of the different assessment software data models, let’s quickly look at some of the top assessment applications available in the market today, which can be integrated with different software like ATS, HRIS, LMS, etc.
Assessment software is a part of the larger ecosystem of software that companies today use to manage their people's operations. Invariably, there are several other tools and software in the market today, which when integrated with assessment APIs can lead to operational efficiency and smooth HR and related processes. There are several categories of tools out there which either feed data into assessment APIs (write APIs) or get access to data from assessment APIs (read APIs). Integration ensures that such data syncs are automated and do not require any manual interview, which can be prone to errors, time consuming and operationally taxing. Here are some of the top use cases for assessment API integration across different software.
Assessment API integration is very critical for ATS or applicant tracking systems. ATS tools and platforms have all the required information about candidates, including their name, profile, pictures, contact information, etc. Assessment API integration with ATS tools ensures that the assessment read API can get access to all these details automatically without any manual intervention. At the same time, integration also facilitates real-time information updation in assessment tools, which can set up assessments for new applicants almost immediately. This leads to faster turnaround. Furthermore, the assessment write APIs can feed information back to the ATS tools with the assessment results and scorecards to help update the candidate’s status in the recruitment flow.
Examples: Greenhouse Software, Workable, BambooHR, Lever, Zoho
Candidate screening tools help organizations determine whether or not a candidate is ideal or right for the role in question. Integration with assessment software ensures that data about a candidate’s performance in an assessment test is automatically synced for screening managers to assess the skills, competencies and abilities of the candidate and its relevance to the open position. Furthermore, assessment API integration with candidate screening tools ensures that the latter have real time access to candidate assessment results for immediate hiring decision making, based on evidence backed data for smart hiring.
Examples:
Assessment API integration with HRIS tools is a no brainer. Once a candidate clears the assessments and is offered a job at an organization, it is essential to capture the results from the assessments in the HRIS platform. Here, the assessment write APIs play an important role. They help HR teams get access to all the relevant information about an employee based on different personality, psychometric, behavioral, cognitive tests to help them capture employee records which are robust and comprehensive. Automated integration of data from assessment tools to HRIS platforms ensures that no human error or bias crawls in when assessment data is being entered into HRIS portals. Furthermore, since many parts of an assessment test can be sensitive, such integration ensures that data exchange is confidential and on a need to know basis only.
Examples: BambooHR, Namely, SAP SuccessFactors, Gusto
Most companies today leverage interview scheduling tools to automate their entire interview processes, including blocking calendars, managing schedules, etc. For interview scheduling tools, integration with assessment APIs is important to ensure that all interviews with candidates can be scheduled effectively, keeping in my mind both interviewer and interviewee schedules. Interview scheduling tools can leverage assessment read APIs to understand the assessment availability and dates to schedule the interview. Furthermore, once the interview is scheduled, assessment write APIs can help provide updates on whether or not the candidate attended the interview, status, next steps to help interview scheduling tools effectively conduct interactions with candidates as needed.
Examples: Calendly, Sense, GliderAI, YouCanBookMe, Paradox
While most assessment software have use cases in the pre-employment stages, their utility can also transcend into post employment phases as well. The LMS tools can easily leverage assessment read APIs to understand the type of assessment tests available which can be used for internal training purposes. Furthermore, candidate performance in pre-employment assessment tests can be used as a baseline to define the types of training required and areas for upskilling. Overall, this integration can help identify the learning needs for the organization and clarify the assessments available for further investigation. At the same time, once the assessments are administered, the assessment write API can automatically sync the relevant data and results for post employment assessment on whether or not employees participated in the assessments, results, gaps, etc. to the LMS tools for better decision making on employee training and development.
Example: TalentLMS, 360Learning, Docebo, Google Classroom
Talent management and workforce planning tools are integral when it comes to succession planning for any organization. Assessments conducted, both pre and post employment can greatly help in determining the talent needs for any organization. Talent management tools can leverage assessment read APIs to understand how their existing or potential talent is performing along areas critical to the organization. Any gaps in the talent or consistent poor performance in a particular area of assessment can then be identified to adopt corrective measures. Assessment API integration can help talent management tools effectively understand the talent profile in their organization, which can further help in better succession planning and talent analytics.
Examples: ClearCompany, Deel, ActivTrak
There are several ways companies can achieve assessment API integration to suit their use cases. Right from building integrations in-house for each assessment tool to practices like workflow automation tools, there are several ways to integrate. However, as the number of customers and integration needs increase exponentially, going for a unified assessment API for integration is the best move. Here are a few instances when choosing a unified API for assessment software integration makes sense. Use unified assessment API when you:
Now that you know a unified assessment API is the best and the most effective for you to build integrations with assessment software, go through the following questions to choose the best unified assessment API for your organization.
The ideal unified API normalizes and syncs data into a unified data model and facilitates data transformation 10x faster. While most fields are common and a unified model works, choose a unified assessment API which also gives you the flexibility to add some custom data models which may not align with the standard data models available.
Each unified API will offer rate limits, which is the number of API requests or data sync requests you can make in a given period of time. Having an optimum rate limit is extremely important. Having a very high rate limit, in which many requests can be made can lead to potential DDoS attacks and other vulnerabilities. Whereas, having a very low rate limit, where only a handful API requests can be made, might lead to inefficiencies and data inaccuracies. Therefore, gauge the rate limits offered to check if they align with your needs or if they can be customized for you.
Next, any unified assessment API you choose should be high on security. On the one hand, check for compliance with all certifications and global standards. On the other hand, look out for comprehensive data encryption, which involves encrypting data at rest and in transit. When looking at security, do check the level of authentication and authorization available.
Building integrations is followed by the operationally and technically draining tasks of managing integrations. Integration maintenance and management can take anywhere between 5-10 hours of your engineering bandwidth. Therefore, choose a unified assessment API provider which provides you with maintenance support. You should be able to manage the health of all your integrations with a robust track of all API calls, requests, etc.
As data sync is the most important part of assessment API integration, check the sync frequency offered by the unified API. While real-time sync, powered by a webhook architecture which ensures real-time data transfer, without any polling infrastructure is ideal. It is equally important to have something which can be customized and allows you to set the sync frequency as per your needs.
The key purpose of a unified assessment API is to scale as fast as possible and ensure all customer assessment tools are integrated with. Therefore, you must check the breadth of assessment API integrations being offered. At the same time, explore how open and forthcoming the unified API provider is to custom integrations for you if needed. This also needs to be weighted against the time taken for each new integration and any cost associated with the same.
Finally, as you add more assessment API integrations and the number of customers using the same increase, the data load for sync will experience an exponential rise. Thus, your unified assessment API must facilitate guaranteed scalability with quality sync, irrespective of the data load. Without the same, there are chances of data corruption.
As a leading unified assessment API, Knit has the right tick mark for all the considerations mentioned above and much more. Here’s why you should consider Knit for your assessment API integration needs:
Book a demo today to learn about the other ways in which Knit can be your ideal unified assessment API partner, how it works and anything else you need to know!
Integrating with assessment APIs can help different companies and platforms unlock value to better streamline their operations. Assessment API integration can facilitate bi-directional sync of data between assessment tools and other applications. While there are several ways to achieve such integration, a unified API is one of the top contenders as it facilitates data normalization, high levels of security, guaranteed scalability, seamless maintenance and management and real time data syncs.
Our detailed guides on the integrations space
If you are exploring Unified APIs or Embedded iPaaS solutions to scale your integrations offerings, evaluate them closely on two aspects - API coverage and developer efficiency. While Unified API solutions hold great promise to reduce developer effort, they struggle to provide 100% API coverage within the APPs they support, which limits the use cases you can build with them. On the other hand, embedded iPaaS tools offer great API coverage, but expect developers to spend time in API discovery for each tool and build and maintain separate integrations for each, requiring a lot more effort from your developers than Unified APIs.
Knit’s AI driven integrations agent combines the best of both worlds to offer 100% API coverage while still expecting no effort from developers in API discovery and building and maintaining separate integrations for each tool.
Let’s dive in.
Hi there! Welcome to Knit - one of the top ranked integrations platforms out there (as per G2).
Just to set some context, we are an embedded integration platform. We offer a white labelled solution which SaaS companies can embed into their SaaS product to scale the integrations they offer to their customers out of the box.
The embedded integrations space started over the past 3-4 years, and today, is settling down into two kinds of solutions - Unified APIs and Embedded iPaaS Tools.
You might have been researching solutions in this space, and already know what both solutions are, but for the uninitiated, here’s a (very) brief download.
Unified APIs help organisations deliver a high number of category-specific integrations to market quickly and are most useful for standardised integrations applicable across most customers of the organisation. For Example: I want to offer all my customers the ability to connect their CRM of choice (Salesforce, HubSpot, Pipedrive, etc.) to access all their customer information in my product.
Embedded iPaaS solutions are embedded workflow automation tools. These cater to helping organisations deliver one integration at a time and are most useful for bespoke automations built at a customer level. For Example: I want to offer one of my customers the ability to connect their Salesforce CRM to our product for their specific, unique needs.
Knit started its life as a Unified API player, and as we spoke to hundreds of SaaS companies of all sizes, we realised that both the currently popular approaches make some tradeoffs which either put limitations on the use cases you can solve with them or fall short on your expectations of saving engineering time in building and maintaining integrations.
But before we get to the tradeoffs, what exactly should you be looking for when evaluating an embedded integration solution?
While there will of course be nuances like data security, authentication management, ability to filter data, data scopes, etc. the three key aspects which top the list of our customers are:
Now let’s try and understand the tradeoffs which current solutions take and their impact on the three aspects above.
The idea of providing a single API to connect with every provider is extremely powerful because it greatly reduces developer effort in building each integration individually. However, the increase in developer efficiency comes with the tradeoff of coverage.
Unifying all APPs within a SaaS category is hard work. As a Unified API vendor, you need to understand the APIs of each APP, translate the various fields available within each APP into a common schema, and then build a connector which can be added into the platform catalogue. At times, unification is not even possible, because APIs for some use cases are not available in all APPs.
This directly leads to low API coverage. For example, while Hubspot exposes a total of 400+ APIs, the oldest and most well-funded Unified API provider today offers a Unified CRM API which covers only 20 of them, inherently limiting its usefulness to a subset of the possible integration use cases.
Coverage is added based on frequency of customer demand and as a stop gap workaround, all Unified API platforms offer a ‘passthrough’ feature, which allows working with the native APIs of the source APP directly when it is not covered in the Unified model. This essentially dilutes the Unified promise as developers are required to learn the source APIs to build the connector and then maintain it anyways, leading to a hit on developer productivity.
So, when you are evaluating any Unified API provider, beyond the first conversation, do dig deep into whether or not they cover for the APIs you will need for your use case.
If they don’t, your alternative is to either use the pass throughs, or work with embedded iPaaS tools - both can give you added coverage, but they tradeoff coverage with developer efficiency, as we will learn below.
While Unified APIs optimise for developer efficiency by offering standard 1: many APIs, embedded iPaaS tools optimise for coverage.
They offer almost all the native APIs available in source systems on their platforms for developers to build their integrations, without a unification layer. This means developers looking to build integrations on top of embedded iPaaS tools need to build a new integration for each new tool their customers could be using. Not only this requires developers to spend a lot of time in API discovery for their specific use case, but also then maintain the integration on the platform.
Perhaps this is the reason why embedded iPaaS tools are best suited for integrations which require bespoke customization for each new customer. In such scenarios, the value is not in reusing the integration across customers, but rather the ability to quickly customise the integration business logic for each new customer. And embedded iPaaS tools deliver on this promise by offering drag drop, no code integration logic builders - which in our opinion drive the most value for the users of these platforms.
**Do note, that integration logic customization is a bit different from the ability to handle customised end systems, where the data fields could be different and non-standard for different installations of the same APP. Custom fields are handled well even in Unified API platforms.
So, we now know that the two most prominent approaches to scale product integrations today, even though powerful for some scenarios, might not be the best overall solutions for your integration needs.
However, till recently, there didn’t seem to be a solution for these challenges. That changed with the rapid rise and availability of Generative AI. The ability of Gen AI technology to read and make sense of unstructured data, allowed us to build the first integration agent in the market, which can read and analyse API documentation, understand it, and orchestrate API calls to create unified connectors tailored for each developer's use case.
This not only gives developers access to 100% of the source APPs APIs but also requires negligible developer effort in API discovery since the agent discovers the right APIs on the developer's behalf.
What’s more, another advantage it gives us is that we are now able to add any missing APP in our pre-built catalogue in 2 days on request, as long as we have access to the API documentation. Most platforms take anywhere from 2-6 weeks for this, and ‘put it on the roadmap’ while your customers wait. We know that’s frustrating.
So, with Knit, you get a platform that is flexible enough to cover for any integration use case you want to build, yet doesn’t require the developer bandwidth required by embedded iPaaS tools in building and maintaining separate integrations for each APP.
This continues and builds upon our history (however small) of being pioneers in the integration space, right since inception.
We were the first to launch a 'no data storage' Unified API, which set new standards for data security and forced competition to catch up — and now, we’re the first to launch an AI agent for integrations. We know others will follow, like they did for the no caching architecture, but that’s a win for the whole industry. And by then, we’re sure to be pioneering the next step jump in this space.
It is our mission to make integrations simple for all.
Organizations today adopt and deploy various applications, to make their work simpler, more efficient and enhance overall productivity. However, in most cases, the process of connecting with these applications is complex, time consuming and an ineffective use of the engineering team. Fortunately, over the years, different approaches or platforms have seen a rise, enabling companies to integrate applications for their internal use or to create customer facing interfaces.
In this article, we will discuss the different options available for companies to integrate with SaaS applications. We will detail the diverse approaches for different needs and use cases, along with a comparative analysis between the different platforms within each approach to help you make an informed choice.
As mentioned above, particularly, there are two types of SaaS integrations that most organizations use or need. Here’s a quick understanding of both:
Internal use integrations are generally created between two applications that a company uses or between internal systems to facilitate seamless and data flow. Consider that a company uses BambooHR as its HRMS systems and stores all its HR data there, while using ADPRun to manage all of its payroll functions. An internal integration will help connect these two applications to facilitate information flow and data exchange between them.
For instance, with integration, any new employee that is onboarded in BambooHR will be automatically reflected in ADPRun with all relevant details to process compensation at the end of the pay period. Similarly, any employees who leave will be automatically deleted, ensuring that the data across platforms being used internally is consistent and up to date.
On the other hand, customer-facing integrations are intrinsically created between your product and the applications used by your customer to facilitate seamless data exchange for maximum efficiency in operations. It ensures that all data updated in your customer’s application is synced with your product with high reliability and speed.
Let’s say that you offer candidate communication services for your customers. Using customer-facing integrations, you can easily connect with the ATS application that your customer uses to ensure that whenever there is any movement in the application status for any candidate, you promptly communicate to the candidate on the next steps. This will not only ensure regular flow of communication with the candidate, but will also eliminate any missed opportunities with real time data sync.
With differences in purposes and use cases, the best approach and platforms for different integrations also varies. Put simply, most internal integrations require automation of workflow and data exchange, while customer facing ones need more sophisticated functionalities. Even with the same purpose, the needs of developers and organizations can be varied, creating the need for diverse platforms which suit varying requirements. In the following section, we will discuss the three major kinds of integration platforms, including workflow automation tools, embedded iPaaS and unified APIs with specific examples within each.
Essentially, internal integration tools are expected to streamline the workflow and data exchange between internally used applications for an organization to improve efficiency, accuracy and process optimization. Workflow automation tools or iPaaS are the best SaaS integration platforms to support this purpose. They come with easy to use drag and drop functionalities, along with pre-built connectors and available SDKs to easily power internal integrations. Some of the leaders in the space are:
An enterprise grade automation platform, Workato facilitates workflow automation and integration, enabling businesses to seamlessly connect different applications for internal use.
Benefits of Workato
Limitations of Workato
Ideal for enterprise-level customers that need to integrate with 1000s of applications with a key focus on security.
An iSaaS (integration software as a service) tool, Zapier allows software users to integrate with applications and automate tasks which are relatively simple, with Zaps.
Benefits of Zapier
Limitations of Zapier
Ideal for building simple workflow automations which can be developed and managed by all teams at large, using its vast connector library.
Mulesoft is a typical iPaaS solution that facilitates API-led integration, which offers easy to use tools to help organizations automate routine and repetitive tasks.
Benefits of Mulesoft
Limitations of Mulesoft
Ideal for more complex integration scenarios with enterprise-grade features, especially for integration with Salesforce and allied products.
With experience of powering integrations for multiple decades, Dell Boomi provides tools for iPaaS, API management and master data management.
Benefits of Dell Boomi
Limitations of Dell Boomi
Ideal for diverse use cases and comes with a high level of credibility owing to the experience garnered over the years.
The final name in the workflow automation/ iPaaS list is SnapLogic which comes with a low-code interface, enabling organizations to quickly design and implement application integrations.
Benefits of SnapLogic
Limitations of SnapLogic
Ideal for organizations looking for automation workflow tools that can be used by all team members and supports functionalities, both online and offline.
While the above mentioned SaaS integration platforms are ideal for building and maintaining integrations for internal use, organizations looking to develop customer facing integrations need to look further. Companies can choose between two competing approaches to build customer facing SaaS integrations, including embedded iPaaS and unified API. We have outlined below the key features of both the approaches, along with the leading SaaS integration platforms for each.
An embedded iPaaS can be considered as an iPaaS solution which is embedded within a product, enabling companies to build customer-facing integrations between their product and other applications. This enables end customers to seamlessly exchange data and automate workflows between your application and any third party application they use. Both the companies and the end customers can leverage embedded iPaaS to build integration and automate workflows. Here are the top embedded iPaaS that companies use as SaaS integrations platforms.
In addition to offering an iPaaS solution for internal integrations, Workato embedded offers embedded iPaaS for customer-facing integrations. It is a low-code solution and also offers API management solutions.
Benefits of Workato Embedded
Limitations of Workato Embedded
Ideal for large companies that wish to offer a highly robust integration library to their customers to facilitate integration at scale.
Built exclusively for the embedded iPaaS use case, Paragon enables users to ship and scale native integrations.
Benefits of Paragon
Limitations of Paragon
Ideal for companies looking for greater monitoring capabilities along with on-premise deployment options in the embedded iPaaS.
Pandium is an embedded iPaaS which also allows users to embed an integration marketplace within their product.
Benefits of Pandium
Limitations of Pandium
Ideal for companies that require an integration marketplace which is highly customizable and have limited bandwidth to build and manage integrations in-house.
As an embedded iPaaS solution, Tray Embedded allows companies to embed its iPaaS solution into their product to provide customer-facing integrations.
Benefits of Tray Embedded
Limitations of Tray Embedded
Ideal for companies with custom integration requirements and those that want to achieve automation through text.
Another solution solely limited to the embedded iPaaS space, Cyclr facilitates low-code integration workflows for customer-facing integrations.
Benefits of Cyclr
Limitations of Cyclr
Ideal for companies looking for centralized integration management within a standardized integration ecosystem.
The next approach to powering customer-facing integrations is leveraging a unified API. As an aggregated API, unified API platforms help companies easily integrate with several applications within a category (CRM, ATS, HRIS) using a single connector. Leveraging unified API, companies can seamlessly integrate both vertically and horizontally at scale.
As a unified API, Merge enables users to add hundreds of integrations via a single connector, simplifying customer-facing integrations.
Benefits of Merge
Limitations of Merge
Ideal to build multiple integrations together with out-of-the-box features for managing integrations.
A leader in the unified API space for employment systems, Finch helps build 1:many integrations with HRIS and payroll applications.
Benefits of Finch
Limitations of Finch
Ideal for companies looking to build integrations with employment systems and high levels of data standardization.
Another option in the unified API category is Apideck, which offers integrations in more categories than the above two mentioned SaaS integration platforms in this space.
Benefits of Apideck
Limitations of Apideck
Ideal for companies looking for a wider range of integration categories with an openness to add new integrations to its suite.
A unified API, Knit facilitates integrations with multiple categories with a single connector for each category; an exponentially growing category base, richer than other alternatives.
Benefits of Knit
Ideal for companies looking for SaaS integration platforms with wide horizontal and vertical coverage, complete data privacy and don’t wish to maintain a polling infrastructure, while ensuring sync scalability and delivery.
Clearly SaaS integrations are the building blocks to connect and ensure seamless flow of data between applications. However, the route that organizations decide to take large depends on their use cases. While workflow automation or iPaaS makes sense for internal use integrations, an embedded iPaaS or a unified API approach will serve the purpose of building customer facing integrations. Within each approach, there are several alternatives available to choose from. While making a choice, organizations must consider:
Depending on what you consider to be more valuable for your organization, you can go in for the right approach and the right option from within the 14 best SaaS integration platforms shared above.
If you are looking to integrate multiple HRIS and ATS apps with a single API , check out Knit API. If you are looking to learn more about key ATS API concepts, data models and use cases, keep reading.
Hiring the right talent is crucial to building a high-performing organization, yet the dynamic nature of recruitment has made this process increasingly complex. To keep up with these challenges, companies now rely on various applications to streamline and automate the hiring journey.
Applicant Tracking Systems (ATS) have become the backbone of this evolving hiring ecosystem, encompassing everything from sending job requisitions to final offer acceptance and onboarding. In fact, 78% of recruiters using ATS report improved efficiency in their hiring process. To further optimize these systems, organizations are increasingly adopting ATS API integrations, enabling seamless data exchange between applications and enhancing the overall recruitment experience.
Read more: What is API integration? (The Complete Guide)
ATS integrations enable smooth communication between various tools—onboarding platforms, job boards, scheduling software, assessment applications, HRIS, payroll systems, and more. Below are a few key examples:
ATS integrations for internal use: Integrating ATS software with assessment software to accelerate candidate testing
For technical roles, companies often require candidates to complete coding or technical assessments via third-party platforms. By integrating the ATS with an assessment portal, any status update in the ATS that triggers an assessment can automatically notify the candidate. This eliminates manual data entry, with results automatically fed back into the ATS, speeding up the next step of the recruitment cycle.
E-signature company building integration with their customer’s ATS platform for smooth onboarding
Companies increasingly use e-signature platforms to send offer letters and manage regulatory formalities. E-signature providers now offer integration with ATS platforms for their customers to automatically receive candidate data once an offer is made, ensuring a smooth onboarding process without the need for manual information transfers.
ATS API integrations are transforming recruitment by simplifying and automating workflows for internal operations and customer facing processes alike. In this article, we’ll explore the different aspects of ATS integration, including key concepts, use cases, data models, best practices, and challenges, to understand how ATS APIs are reshaping the future of hiring.
ATS API integration offers significant advantages for both internal teams and external partners. By streamlining the recruitment process, it enhances efficiency, accelerates hiring timelines, and minimizes resource expenditure. Below are the top benefits of implementing ATS API integrations:
One of the key benefits of ATS API integration with other recruitment tools is the reduction in recruitment time. By eliminating the need to manually update information across portals, organizations can accelerate the pace at which candidates move to the next stage. This ensures that the positions get filled faster. The time to hire becomes shorter, minimizing delays, and ensuring open positions are filled faster while reducing the risk of losing top talent due to slow processes.
Beyond recruitment, ATS API integration speeds up onboarding and provisioning for new hires. By connecting ATS with onboarding platforms such as e-signature tools or document verification systems, companies can expedite the process of getting employees operational. Additionally, API integration automates provisioning tasks, such as assigning software access, permissions, and licenses based on role and department, ensuring new hires are equipped to start contributing sooner. Invariably, this helps companies ensure that their new employees are productive from day one.
Even minor mistakes in recruitment can have significant consequences, potentially derailing the entire hiring process. For example, a single-digit error in a salary offer can not only frustrate candidates but also impact the company’s financial stability. By automating data transfers and reducing the need for manual entry, ATS API integration significantly lowers the risk of these costly errors. This automation ensures accuracy throughout the hiring process, safeguarding the organization from both financial losses and reputational damage.
ATS API integration allows companies to generate comprehensive reports on hiring patterns and workforce dynamics by connecting ATS with other HR and recruitment platforms. This integration provides real-time access to data, making it easier to track key metrics like time-to-hire, cost-per-hire, and candidate conversion rates. For instance, integrating ATS with a Learning Management System (LMS) helps identify skills gaps in new hires. Similarly, the integration of ATS with Employee Resource Planning (ERP) systems can provide insights into long-term workforce needs to make more informed decisions about resource allocation and recruitment priorities.
ATS API integration improves the experience for both candidates and recruiters by streamlining processes and reducing manual tasks. Candidates benefit from a smoother, more standardized hiring journey with faster feedback, thanks to automated workflows. For recruiters, integration eliminates the need for manual data entry and allows quick access to candidate information across platforms. This lets them focus on hiring top talent and closing more positions in less time, boosting both productivity and job satisfaction.
By leveraging ATS API integration, organizations can optimize their recruitment processes, drive efficiency, and ensure smoother hiring and onboarding experiences for all stakeholders.
The first step to facilitate ATS integration is to understand the different ATS concepts that can help you familiarize yourself with the right terminology.
Even before an organization starts receiving and processing applications, a key concept to understand is job requisition. Essentially, a job requisition is a template or a form which contains all the details about the job for which applicants are being sought. This includes details on the requirements as well as the process of closing the positions, like assessments, interviews, etc. It may also include details of the hiring manager and other relevant information. Different apps can have different ways of assigning job requisitions.
Sourcing and mapping starts once the job requirements become clear. The HR or the recruitment manager generally navigates through different platforms and candidate pools to identify the right candidates and map them to different openings within the organization. Sourcing is when the hiring manager proactively reaches out to qualified candidates for a specific job opening.
These three are integral concepts for any ATS API. While the terminology might change slightly for different applications, you will find all of these in some essence.
Another set of concepts come into play when the communication with a candidate begins.
Most ATS apps have specific data models which they use to streamline workflow and dataflow. As a unified API for ATS integration, Knit focuses on the following data models for ATS API:
Contains all applicant details like job ID, status, owner, credited to (who receives credit for the application), applied at, updated at, etc. It also contains information about the candidate, location, links and documents attached, among others.
The stage at which the applicant is currently at, ranging from applied to selected or rejected with a stage ID and stage name.
Keeps all the information regarding a candidate's interview, when it is scheduled for, start time, end time, status, list of interviewers, location, etc.
Contains data and information about any rejected application or candidate, including job ID, reason for rejection, rejected at which stage, etc.
All the offers extended to an application. It contains the details about the offer as well as the status to define whether the offer has been extended, signed, declined. It also keeps data on when the offer was extended, when it was closed, etc.
Application resume or attachments refers to all the documents (such as resume, cover letter etc) which are associated with a particular candidate or application. They are present in the form of downloadable links and when it was created.
Along with these application data models, Knit also offers several key job data models. For more details, check our documentation
Successful ATS integration requires a clear grasp of key concepts and the adoption of best practices throughout the development and maintenance phases. Here are essential practices for developers to consider:
Start with an in-depth understanding of the ATS API you plan to integrate with. This involves not only grasping communication protocols and authentication methods but also performing market research on its penetration, security measures, reliability, and performance history. Access to comprehensive, up-to-date API documentation is critical for understanding functionality, endpoints, rate limits, and troubleshooting potential errors. High-quality documentation, which is clear and easy to understand, is the foundation for building and maintaining seamless integrations.
Once developers have a clear understanding of the APIs they want to integrate with, creating a comprehensive integration plan is critical. Prioritize which ATS integrations to tackle first and adopt a phased approach for rolling out each integration. Clearly define timelines to help allocate resources effectively and mitigate conflicts with core product development. Ensuring stakeholder alignment and securing buy-in is essential for smooth execution.
While building integrations is the first step, it is important to ensure rigorous testing in different environments and across diverse use cases. This helps prevent API errors which can lead to significant downtime and even compromise the performance of your applications. While the ATS may have its own testing protocols, however, it is ideal to conduct internal testing to ensure smooth performance and address issues proactively. In addition to ensuring smooth and error free functioning, your testing should also include capturing remediation steps in case errors crop up. Implement continuous monitoring and logging to catch and rectify errors over time, ensuring your integration remains stable and reliable.
Read more: API Monitoring and Logging
Scalability should be an integral consideration from the beginning of ATS API integration. As your business grows, so will the need to not only support more ATS systems but also to expand the scope and functionality of existing integrations. This can include adding new features, supporting larger volumes of data, or connecting to more complex workflows as the requirements of your customers evolve. To achieve scalability, it's crucial to design your API integrations with flexibility and extensibility in mind. This may involve modularizing your codebase so that adding new ATS systems or features doesn’t require overhauling the entire integration. Your system should be able to handle an increasing number of API calls and larger datasets without compromising response time or stability.
Despite the best efforts in testing, certain errors are likely to crop up from time to time. While it is critical to continually invest in increasing the testing coverage, it is equally important to develop and educate your internal and external stakeholders about handling common errors. Develop error-handling mechanisms that are not only effective but also simple enough to understand and can be executed by non-technical and customer facing teams as well. This will help reduce the burden of all error handling on developers, enabling them to focus on core product functionalities. This requires thorough documentation which not only captures the remediation steps but also explanations of their root causes. Continuous logging and monitoring of errors will help identify and address recurring issues over time.
It is also important for developers to weigh in all engineering priorities to decide whether to build and maintain ATS API integrations in-house or to outsource them. Today, there are several external integration tools that are available to help building and maintaining ATS integrations. While iPaaS or workflow automation tools can help with internal integrations, embedded iPaaS and unified APIs are ideal for customer facing integrations. Increasingly, developers are inclining towards ‘buying’ integrations as tools like unified APIs can help connect with most ATS applications with a single connector, enabling speed to scale, while taking care of all authentication, communication protocols, management and everything else.
Read more: Whitepaper: The Unified API Approach to Building Product Integrations
By following these best practices, developers can create robust, scalable, and efficient ATS API integrations that deliver lasting value.
By now you understand that there are several layers to the ATS integration with different types of applications. Here are the top ATS APIs which you should consider connecting with to make hiring smooth and streamlined for your organization.
1. Job posting APIs
The first set of ATS integration you should look out for is the one which can help you with job posting. This involves ensuring that your company profile and job openings are visible to potential candidates to generate interest and leads.
Top job posting ATS API: Indeed, Monster, Naukri, The Muse
2. Candidate/ Lead sourcing APIs
Once the job has been posted, the next step is to build a pipeline of potential candidates. ATS applications for candidate and lead sourcing help extract important candidate data for profile matching, referrals, etc.
Top candidate sourcing ATS API: Zoho, Freshteam, LinkedIn
3. Resume parsing APIs
The next step after candidate sourcing is resuming sorting. Here resume parsing applications make sense for your ATS integration. These help with automated collection, storage and filtering of resumes. Resume parsing ATS APIs can help extract relevant information from resumes like skills, expected salary, previous experience, etc. to help align candidate profiles with job requirements.
Top resume parsing ATS API: Zoho Recruit, HireAbility, CVViz
4. Interview management APIs
Resume screening needs to be followed by interviews to identify a role-fit for the candidates. However, interview management can be extremely complicated. ATS APIs for interviews help address all challenges, including assessments to gauge technical skills, scheduling, managing interview related travel information, etc.
Top interview management ATS API: Calendly, HireVue, HackerRank, Qualified.io, Talview
5. Candidate communication APIs
Communicating effectively with the candidates is extremely important during the whole hiring process. ATS APIs for candidate communication can help automate email, text and other messages and keep track of all interactions in a streamlined manner.
Top candidate communication ATS API: Grayscale, Paradox
6. Offer extension and acceptance APIs
Finally, once you decide to onboard a particular candidate, you need relevant ATS integration for extending the offer where the candidate can accept the same and share any document(s) that you might need for onboarding. Offer acceptance applications facilitate electronic signatures, and other formalities in a seamless manner.
Top offer extension and acceptance ATS API: DocuSign, AdobeSign, DropBox Sign
To check out Knit’s entire ATS and HRIS API catalog click here
7. Background verification APIs
When you are extending an offer, it is very important to ensure background verification or check for your potential employees. While you may have performed initial reference checks when you received the application, while hiring someone, you need to get a more comprehensive understanding of their profile. Doing this manually can be extremely time and resource extensive.
Here, ATS integrations for background verification can help you run a check based on your required parameters on the candidate profile and flag any concerns if they appear. This way, you can be rest assured that the employees who come on board don’t have any form of ethical or legal or any other baggage.
Top background verification ATS API: Certn, Hireology, HireRight, GoodHire
8. Analytics and reporting APIs
Now that your hiring is complete, you should analyze the entire process to gauge where you stand in terms of open positions, the DEI status for your organization, overall headcount, etc. ATS integration for analytics and reporting can help you get dashboard with all such information
Top analytics and reporting ATS API: LucidChart, ChartHop
Read more: How to Automate Recruitment Workflows with ATS APIs and Hire Smarter
One of the biggest benefits of ATS integration is that organizations are easily able to integrate a lot of data about the candidate and terms of hiring with significant new use cases.
On one hand, organizations can internally use this data for better decision making and ensure effective human resources distribution. On the other hand, this data can become the foundation for other companies to facilitate seamless business continuity across industries.
In this section, we will discuss the top ATS API use cases that SaaS companies are applying today.
I) Seamless onboarding
The first major use case for data from ATS APIs revolves around onboarding and building of HRIS data. With ATS integrations, important data about the candidate like demographic information, qualifications, documents, attachments, identity proofs etc. which are collected during the course of applicant tracking can be automatically transported to the HRMS or HRIS. Furthermore, the salary details and other terms of employment as shared during offer extension can also be communicated to the payroll APIs.
This brings along twin benefits.
II) Compensation management
As mentioned, ATS API integrations can ensure that all details about the candidate compensation are shared with the payroll application to facilitate correct salary calculation and on-time disbursement. This is specifically useful if you are on a mass hiring mode and don’t want to delay your payroll.
Furthermore, compensation data from your ATS, not only for the selected candidates but also the salary expectations and other details can help you ensure fair and equitable compensation management. This data can help you understand what the market expectations are and how you are able to address the same. Similarly, data from ATS API can help gauge discrepancies or differences that might crop up across gender, experiences, level of seniority. Invariably, this data can help you facilitate fair pay based on market standards to attract the best talent.
At the same time, third party companies which are experts in compensation management and consulting can integrate this data with their findings to help you with the best practices.
III) Diversity and inclusion
An essential part that you need to focus on during hiring and afterwards is the diversity and inclusion aspect of your workforce. The ATS API data can help you understand the diversity of the candidate pool vis-a-vis the final hiring and closing of positions. Based on this data, your internal DEI team or external experts can help you understand if there is a leakage of diversity along the way.
Invariably this will encourage you to understand if some part of your hiring process is biased or if you are using ATS applications which are not inclusive enough. You can identify the positions or roles where your diversity ratio is specifically low to understand the concerns. Simultaneously, you can make conscious efforts to bridge this lack of diversity.
IV) Automated job posting
ATS API data will be incredibly helpful in automating the job posting process. For instance, data from interviews and other applications can indicate the pipeline of candidates and their status. In case the pipeline for a particular role is getting extremely weak with a lot of rejections during interviews or offer acceptances, your ATS application for job boards can be triggered for job posting followed by candidate sourcing and resume parsing.
Here, the idea is to reduce manual time that goes into identifying which roles are still open and doubling down efforts on sourcing candidates for the same. This will only be possible when you can get real time data with continuous sync from your ATS APIs about the status of different candidates and applications.
Read more: How Interview Scheduling Companies Can Scale ATS Integrations 10X Faster
While ATS API integrations offer numerous benefits, developers and teams often encounter significant challenges. These include:
One of the major challenges in ATS API integration is managing incompatible data formats between different systems. Various applications may use different syntax or naming conventions for the same data fields, such as candidate_ID in one system versus cand_ID in another. Without proper data normalization, these discrepancies can lead to critical issues like data duplication, loss, or inconsistency during transfers. For example, some fields might not match up correctly, causing crucial recruitment data to go missing or become corrupted. Developers are often forced to spend a significant amount of time transforming data to ensure it aligns across different systems. Even with diligent normalization efforts, some data might still be lost or altered in transit, which can have far-reaching impacts on the recruitment process. Missing or incomplete candidate profiles can result in recruitment delays and even the loss of qualified candidates, making data management a critical issue.
Data sync is critical for ensuring timely recruitment processes, but ATS API integrations often face delays due to rate limiting, throttling, or inefficient retry mechanisms. These factors can slow down syncing of candidate data between systems, especially when handling large volumes of information. Inconsistent data syncs may lead to applications being partially transferred or, worse, lost during the recruitment process. For example, if the ATS doesn't sync with internal HR systems in near real-time, recruiters may not have access to the latest candidate information when it matters most. This can cause delays in shortlisting, interviewing, and onboarding, which ultimately slows down the entire recruitment lifecycle. Furthermore, inconsistent data sync can lead to missing key candidate applications, especially for in-demand roles, which could result in losing high-quality talent to competitors who have more efficient systems in place.
Developing ATS API integrations in-house or partnering with less-experienced vendors can significantly extend both time and cost. On average, building a single API integration can cost over $10K, which includes developer salaries, quality assurance testing, and management oversight. The process often takes around four weeks, meaning core product development is frequently delayed or paused entirely to accommodate the integration efforts. This becomes especially problematic as businesses grow and need multiple ATS integrations to keep pace with client demand. As a result, companies quickly find that the time and financial burden of managing integrations in-house becomes unsustainable. Each additional integration compounds the problem, consuming more resources and further delaying essential product features. Over time, these prolonged development cycles and escalating costs make it increasingly difficult to maintain product scalability and remain competitive in the recruitment software market.
Maintaining a consistent user experience across integrated systems is another challenge with ATS API integration. When users move from the core platform to an integrated ATS system, discrepancies in design, navigation, and functionality can create a disjointed experience. For example, while the core product might have a sleek, modern design, the ATS interface could feel outdated or difficult to navigate, frustrating both internal users and external customers. This lack of consistency can lower user satisfaction and may result in lower engagement rates with the integrated system. Creating a seamless UX across these systems often requires additional time and effort, such as custom branding and interface adjustments for each new integration. The more complex these systems become, the higher the cost and time investment, making ATS integrations not only challenging to implement but also costly to maintain in-house, especially for scaling companies.
Another major hurdle in ATS API integration is the lack of adequate support from ATS vendors. Many ATS platforms offer incomplete or outdated API documentation, which makes it difficult for developers to implement and maintain integrations efficiently. Even when documentation is provided, it often lacks details on newer software versions or critical integration processes, leaving developers to rely on guesswork. Furthermore, real-time support from vendors during integration failures or technical issues is rare. Without immediate assistance, developers are left troubleshooting on their own, which can delay the integration process and disrupt user experience. This lack of support can lead to prolonged downtime or data sync errors, negatively impacting both recruitment teams and candidates. For customer-facing integrations, these disruptions can result in poor product performance, a compromised user journey, and even a potential loss of business if issues remain unresolved for too long.
Knit provides a unified ATS API that streamlines the integration of ATS solutions. Instead of connecting directly with multiple ATS APIs, Knit allows you to connect with top providers like Keka ATS, ADP Workforce Now ATS, BambooHR ATS, Bullhorn, Greenhouse, Darwinbox ATS, Workday ATS API and many others through a single integration.
Learn more about the benefits of using a unified API.
Getting started with Knit is simple. In just 5 steps, you can embed multiple ATS integrations into your App.
Steps Overview:
For detailed integration steps with the unified ATS API, visit:
As mentioned in one of the preceding sections, developers can choose from different alternative approaches to build and management ATS API integrations. Especially, from a customer facing integrations perspective, developer’s can either use direct connectors i.e. build integrations in-house or leverage a unified API like Knit’s ATS API to connect with the preferred ATS applications. Here is a detailed comparison to help you choose between these.
Start by analyzing the number of ATS tools you wish to connect with. Depending on the volume of integrations needed as well as their functionalities and scope, the choice between Knit’s unified API versus direct connector API will become easier.
Use Knit’s ATS API: Need to connect with a wide variety of ATS applications, which have different use cases, data syntax, communication protocols and authentication models
Use Direct connector API: Need to connect with only a select few ATS tools where you have complete access to API documentation and wish to retain complete control over the code
Next, building and maintaining ATS API integrations requires a high level of domain expertise for ATS. There are several terminologies, concepts and nuances that developers need to understand to ensure integration with different ATS tools and their own product.
Use Knit’s ATS API: When developer’s have limited ATS domain expertise and don’t understand the concepts well; When developer’s don’t have the bandwidth to upskill themselves with ATS concepts and knowledge
Use Direct connector API: When developer’s have deep expertise and understanding of ATS related concepts and are able to keep pace with new developments in the field
The decision between using a unified ATS API versus a direct connector will also depend on how urgent the integration requirement is and whether or not there is a need to scale over time as well as the proposed timelines for scalability
Use Knit’s ATS API: When you wish to go live with ATS API integration within a few days and don’t have enough resources at hand to manage the integration process; When you wish to connect with multiple ATS applications with a single connector, unlocking scale at an accelerated pace, i.e. when connecting with multiple integrations fast is imperative
Use Direct connector API: When you have sufficient time in hand to roll out integrations (each integration can take ~4 weeks to build) and the integration requirement is restricted to a few, i.e. you don’t wish to add many new ATS integrations to your offerings in a short span of time
Costs and resources that are required for building and maintaining integrations can be a key deciding factor when it comes to choosing the right integration approach. Depending on the availability of budgets as well as the availability of human resources, developer’s can choose which way to go.
Use Knit’s ATS API: When you don’t want to spend a huge amount for each integration you build; When you don’t have free engineering bandwidth to invest in projects other than core product functionalities, or you don’t want to dilute the core tech roadmap
Use Direct connector API: When you have enough budgets to build and manage integrations (each integration costs ~$10K); When you have enough engineering bandwidth to accommodate integration development without diluting the core tech roadmap and priorities
To ensure consistency in data sync with high quality integration performance, normalizing and transforming data across different data models is extremely important. Furthermore, the choice you make should also ensure guaranteed scalability in data sync, irrespective of data load, without compromising on the quality of the sync.
Use Knit’s ATS API: When you want all data normalized at 10x speed across all ATS applications without investing any developer bandwidth; When you want to ensure webhook based architecture and eliminate the need to maintain a polling architecture; When you want to leverage automatic retry mechanism at regular intervals when rate limits kick in
Use Direct connector API: When you have enough developer bandwidth to normalize data from each ATS application under use; When you can manage retries in data sync, without exploiting the integration in-house
ATS applications use different protocols, like REST, SOAP, GraphQL, etc. and the same holds true for authentication methods, including OAuth, API keys, Passwords, etc. Managing diverse communication and authentication protocols can be a deciding factor between unified APIs versus in-house development.
Use Knit’s ATS API: When you want to outsource the headache of managing different communication and authentication protocols and wish to only expose your developer’s to one unified model for all ATS applications
Use Direct connector API: When you have the bandwidth and the expertise to build integrations corresponding to different protocols, which not only requires time, but also significant domain knowledge
Security is a big concern when it comes to managing integrations. Managing the secure transmission of candidate data is critical to ensure legal compliance as well as candidate delight.
Use Knit’s ATS API: When you want to encrypt your data when in transit as well as when at rest, without any additional engineering efforts from your end; When you want to use a third-party tool, but without the risk of any data being stored in its servers
Use Direct connector API: When you can manage complete encryption and data security in-house with the right expertise, tools and can ensure elimination of human errors which become major causes of security breaches.
How you intend to maintain and manage your integrations will also define your decision to buy vs build ATS API integration.
Use Knit’s ATS API: When you want to ensure automated and effective monitoring and logging for all APIs and get access to a detailed Logs and Issues dashboard i.e. a one page overview of all your integrations, webhooks and API calls
Use Direct connector API: Have enough resources with technical knowledge to not only log errors, but to also offer real time guidance to to your end customers for troubleshooting and resolution
Read more: How Candidate Screening Tools Can Build 30+ ATS Integrations in Two Days
As mentioned above, security is one of the major concerns when it comes to ATS API integration development and management. Here is a quick list of the top security concerns and some of the best practices to mitigate the same.
Read more: Quick Guide to API Lifecycle Management and Decommissioning
Knit’s approach to security:
The evolving and dynamic nature of the recruitment landscape is pushing companies to build integrations with ATS tools, be it for internal use or to position it as a customer-facing offering. ATS API integration accelerates the entire recruitment process, helps create a delightful experience for candidates and recruiters and ensures that new employees can be productive from day one. Whether it is connecting job boards with ATS API to accelerate candidate sourcing or integrating onboarding tools with ATS applications to automate the process of employee provisioning, there are several use cases for ATS API integration.
However, these benefits are accompanied by a set of challenges in terms of data sync inconsistency, data transformation, interface issues, data incompatibility, limited vendor support, etc. Invariably, companies are looking for alternate options to building ATS API integrations in-house and are adopting unified APIs like Knit to outsource the same. Knit’s ATS API helps companies to:
Connect with one of our experts to discover how Knit’s ATS API can serve your ATS integration needs.
Curated API guides and documentations for all the popular tools
CharlieHR is a comprehensive human resources software solution tailored specifically for small businesses, aiming to streamline and automate HR tasks with ease. Designed with user-friendliness in mind, CharlieHR offers a suite of features that simplify the management of HR activities such as onboarding new hires, managing time off, performance management, and conducting engagement surveys. The platform also handles perks and benefits, making it a versatile tool for both managers and employees to navigate their HR responsibilities efficiently.
With a focus on small businesses, CharlieHR provides essential tools for tracking time off and sick leave, as well as monitoring employee work schedules. Its secure data storage and intuitive interface allow users to view, action, and report on various HR aspects effortlessly. Trusted by over 7000 companies, CharlieHR is renowned for its ability to empower teams to manage their own HR activities, reducing the need for a large HR department and enabling businesses to build high-performing teams. For those looking to integrate CharlieHR into their existing systems, the CharlieHR API offers seamless integration capabilities, enhancing the software's functionality and adaptability.
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Notes
How do I generate API keys in CharlieHR?
What authentication method does the CharlieHR API use?
Are there rate limits for the CharlieHR API?
Can I retrieve employee data using the CharlieHR API?
Does the CharlieHR API support webhooks for real-time data updates?
Knit API offers a convenient solution for quick and seamless integration with CharlieHR API. Our AI-powered integration platform allows you to build any CharlieHR API Integration use case. By integrating with Knit just once, you can integrate with multiple other ATS, CRM, HRIS, Accounting, and other systems in one go with a unified approach. Knit handles all the authentication, authorization, and ongoing integration maintenance. This approach saves time and ensures a smooth and reliable connection to CharlieHR API.
To sign up for free, click here. To check the pricing, see our pricing page.
HiBob is a cutting-edge human resources management software that revolutionizes the way businesses handle HR tasks. Known as "Bob," this platform offers a comprehensive suite of features designed to streamline HR processes and enhance employee management. From onboarding workflows to time and attendance management, HiBob provides tools that simplify the complexities of HR operations. Its robust capabilities also include compensation analysis, performance reviews, and workforce planning, making it an indispensable asset for modern HR departments.
One of the standout features of HiBob is its ability to integrate seamlessly with other systems through the HiBob API. This integration capability allows businesses to connect HiBob with their existing software infrastructure, ensuring a smooth flow of data and enhancing operational efficiency. By leveraging the HiBob API, companies can customize their HR processes, automate repetitive tasks, and gain valuable insights into their workforce, ultimately driving better decision-making and fostering a more engaged and productive work environment.
How do I get started with the HiBob API?
What authentication method does the HiBob API use?
Are there rate limits for the HiBob API?
Can I retrieve employee data using the HiBob API?
Does the HiBob API support webhooks for real-time data updates?
Knit API offers a convenient solution for quick and seamless integration with HiBob API. Our AI-powered integration platform allows you to build any HiBob API Integration use case. By integrating with Knit just once, you can integrate with multiple other ATS, CRM, HRIS, Accounting, and other systems in one go with a unified approach. Knit takes care of all the authentication, authorization, and ongoing integration maintenance. This approach not only saves time but also ensures a smooth and reliable connection to HiBob API.
To sign up for free, click here. To check the pricing, see our pricing page.
Bullhorn is a leading software company specializing in providing web-based solutions tailored for the staffing and recruiting industry. Its comprehensive platform is designed to streamline recruitment processes, automate workflows, and ultimately enhance business growth by increasing placements. By leveraging Bullhorn, staffing professionals can efficiently manage candidate relationships, job orders, and client interactions, all within a single, intuitive interface. This focus on automation and efficiency makes Bullhorn an invaluable tool for recruitment agencies aiming to optimize their operations and achieve better results.
A key feature of Bullhorn's offering is its robust Bullhorn API, which allows for seamless integration with other software systems. This API enables businesses to customize their recruitment processes further and integrate Bullhorn's functionalities with existing tools and platforms. By utilizing the Bullhorn API, companies can enhance their data management capabilities, improve communication between different systems, and create a more cohesive recruitment ecosystem. This integration potential is a significant advantage for organizations looking to tailor their recruitment strategies to meet specific business needs.
How do I get started with the Bullhorn REST API?
What authentication method does the Bullhorn API use?
Are there rate limits for the Bullhorn API?
Can I retrieve candidate information using the Bullhorn API?
Does the Bullhorn API support webhooks for real-time data updates?
Knit API offers a convenient solution for quick and seamless integration with Bullhorn API. Our AI-powered integration platform allows you to build any Bullhorn API Integration use case. By integrating with Knit just once, you can integrate with multiple other ATS, CRM, HRIS, Accounting, and other systems in one go with a unified approach. Knit takes care of all the authentication, authorization, and ongoing integration maintenance. This approach not only saves time but also ensures a smooth and reliable connection to Bullhorn API.
To sign up for free, click here. To check the pricing, see our pricing page.