Case study · HR tech
AI candidate screening and matching for an HR tech startup
An HR tech startup processing thousands of applications a month needed recruiters to spend less time screening CVs. We built resume parsing, job matching and an automated shortlisting workflow.
Context
The client and the situation.
The client helps companies hire for technology, finance and operations roles. It handles thousands of applications each month, and its value to employers depends on presenting strong candidates quickly.
Challenge
What was holding them back.
- Recruiters spent hours reading and screening CVs by hand.
- Matching between candidates and roles was inconsistent.
- Shortlists took too long, so strong candidates accepted other offers.
- The cost per hire grew with every new client.
Approach
How we framed the problem.
We combined AI matching with workflow automation. The system parses and scores candidates. Recruiters stay in control of the shortlist, and the routine steps around it are automated.
What we built
The product, module by module.
Resume screening engine
Parses CVs, extracts skills, experience and intent, and scores each candidate against the role.
Matching algorithm
Ranks candidates by skills alignment and experience relevance, and improves from recruiter feedback.
Recruiter dashboard
Ranking, filters, shortlist suggestions and a pipeline view for every open role.
Candidate experience
A simpler application flow, real-time status updates and personalized job suggestions.
Workflow automation
Auto-shortlisting, interview scheduling and notifications.
Results
What changed.
Results reported for the project after launch.
Technology
Stack used.
- React
- Next.js
- Node.js
- PostgreSQL
- NLP resume parsing
- Matching algorithms
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