Talent Intelligence for
Applicant Tracking Systems

Improve your hire rates with deeper understanding of the talent you have, and the talent you have to find.

With Rosette in your ATS you can search resumes and professional sites like LinkedIn for skills, qualifications, and more to uncover hidden talent and improve candidate submissions.


  • Lower TTF (time to fill): smarter candidate search means simpler queries and better results.
  • Higher SHR (submission to hire ratio): deeper understanding of both candidate and job order talent profiles improves matching logic.
  • Higher fill rates: ability to extract candidates from public sites adds additional high-quality candidates to your candidate pool.
  • Higher FYQ (first year quality): discovering how employees feel about a company from sites like Glassdoor adds insight to your client relations.

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7 ATS Functions that Need Text Analytics

  1. Finding candidates to match job orders on the first search without lengthy Boolean queries
  2. Parsing resumes to pull out skills and how they relate to experience
  3. Parsing job orders to pull out qualifications and their context
  4. Mining public content for potential candidates based on their qualifications
  5. Verifying candidate accuracy with public sites like LinkedIn
  6. Calculating company sentiment from review sites like Glassdoor
  7. Calculating candidate sentiment from internal candidate interviews

Mining Candidates from Public Sites

The most desirable candidate isn’t looking for a job. Mining public content is strategic to improving the quality of your candidate submissions and expanding your candidate pool. Public sites worth mining:

  • Code publication sites like GitHub (languages, platforms, protocols)
  • Accredited publication sites like Journal of the AMA
  • New hire and merger and acquisition press announcements

Rosette Text Analytics and Relationships

Rosette, from Basis Technology, is a text analytics engine that can be trained using AI to mine deep into candidate and job order content, extracting skills, qualifications, employment history, education, and more, including relationships like the following:


From Job Order Posting:

  1. Experience configuring systems in AWS EC2 cloud
  2. Managed sales team for legal firms
  3. Experience implementing data analysis for the chemical industry

From Resume:

  1. Responsible for installing and configuring large grid in AWS EC2
  2. Managed sales team for large legal firm
  3. Joined DuPont as Data Analyst





CareerBuilder operates the largest job board in the U.S. They wanted to deliver a better user experience in two ways: user-initiated search and automated recommendations. In switching from FAST to Solr, they were not getting the accuracy they wanted in searches. They learned through FAST that FAST used Basis Technology for their CJK text analysis. As a result of a bake-off between Rosette and plain Solr and Solr with stemming, Rosette’s linguistic analysis (lemmatization, decompounding) increased search accuracy to the FAST baseline and produced better precision and recall. Rosette gives them an edge when their users (job hunters, recruiters) can find better matches for their requirements. Read more about this case study.