Fetcher, an AI candidate sourcing tool for recruiters, needed to build integrations with customers’ applicant tracking systems (ATSs).

Through the integrations, Fetcher could support several key use cases for their users: 

• Users can automatically post candidates to their ATSs based on predefined rules (e.g., a candidate in Fetcher responds to a message sent via the platform) 
• Fetcher can get updates on candidates from integrated ATSs, which would improve Fetcher’s machine learning model for each customer 
• Fetcher can avoid creating duplicate candidates in customers’ ATSs

Their first integrations “were typically dependent on the customers we were working with and how quickly we could get an integration set up,” says Taylor Bold, a Product Manager at Fetcher. But building in-house was difficult due to partnerships and needing significant engineering resources to build and maintain the integrations. 

After building a few core integrations, including Greenhouse, Lever, and SmartRecruiters, and receiving pressure from sales to add more, the Fetcher team decided they needed to find an alternative path or risk not being able to retain customers and grow the company.

Chris Calmeyn, the CPO and co-founder at Fetcher, adds additional context on their decision to outsource their ATS integrations:

After spending a few weeks building to Merge’s ATS Unified API, they were able to add more than 20 ATS integrations to their product. This includes widely-used solutions like Jobvite and iCIMS, along with solutions that are popular in specific regions and industries, like Recruitee (Europe) and Recruiterflow (recruiting and staffing firms).

Here’s how their integrations work:

1. A user would navigate to Integrations and then click on their ATS.

This would prompt Merge Link to pop-up. The user would then follow the steps outlined in Merge Link to authenticate and authorize the ATS integration they want to add.

2. Once the connection gets established, Merge initially adds candidates that are ready for the recruiting team in the customer’s ATS solution. The candidates' ATS profiles could include their first and last names, links to their Linkedin profiles, their current employers and job titles, a source field (populated with Fetcher), etc.

It’s worth noting that if the candidate already exists in the customer’s ATS solution, Merge would only add/update information in their profile.

3. All of the changes in the candidate’s ATS profile (e.g., a candidate signs their offer letter) are posted to Fetcher’s backend. Fetcher then feeds this data to their machine learning model, allowing it to source even better candidates for customers. 

This bidirectional sync runs continually every day. The high frequency empowers customers’ recruiting teams to follow up with target candidates fast and enables Fetcher to improve its AI-powered recommendations quickly and consistently.

Using Merge, Fetcher has been able to scale their ATS integrations significantly faster.

“Merge has allowed us to add ATS integrations 7x faster than we could if we tried building them in-house,” says Chris.

Their team has seen such a big difference that they ended up deciding to migrate all of their in-house integrations to Merge.

Chris further explains why they made that decision:

“Over the past few years, we’ve developed a deep trust for the team at Merge and their ATS integrations. This made the decision to move all of our in-house integrations—which include Greenhouse, Lever and SmartRecruiters—to Merge easy.”

Finally, the team at Fetcher appreciates how Merge’s support team goes above and beyond and continues to improve. 

Chris provides an example that drives this point home:

So, what’s next in Fetcher’s integration journey?

According to Chris, Merge is going to support their team in launching an exciting feature that lets users assess applicants. 

Here’s how it’ll work:

“We’ll post customers’ inbound applicants to Fetcher via Merge’s ATS integrations. We’ll then use AI to evaluate candidates' applications based on the requirements for the role, and, based on the assessments, provide applicants with quality of fit ratings. Recruiters can then use these ratings to determine the candidates they should move forward with,” says Chris.

We look forward to helping Fetcher launch this innovative feature.