Eliminate hiring bias with AI-powered blind evaluation
FairMatch uses intelligent, multi-agent evaluation pipelines to screen candidates on pure merit, hiding PII to prevent implicit bias. Great candidates no longer get lost in the noise, and companies stop wasting hours manually parsing formatted resumes.Quickstart
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How it works
Learn about our multi-agent evaluation system
Key features
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Why FairMatch?
Traditional hiring processes are plagued by unconscious bias, slow screening times, and inaccurate skill assessments. FairMatch solves these problems through three core innovations:Blind evaluation mode
Blind evaluation mode
FairMatch masks PII (names, emails, genders) during the evaluation phase so you can rank candidates strictly on their technical scores. No more unconscious bias creeping into your hiring decisions.
Multi-agent AI engine
Multi-agent AI engine
We utilize a fleet of specialized AI agents running in parallel to generate a comprehensive 360° candidate report. Each agent focuses on what it does best:
- Resume Analyst extracts structured data
- GitHub Verifier validates technical contributions
- Interview Grader assesses responses
- Decision Intelligence provides hiring recommendations
- Integrity Analyst flags potential fraud
Automated PDF parsing
Automated PDF parsing
Rapidly extract structured metadata from uploaded applicant PDFs to feed directly into the AI engine. No more manual data entry or formatting headaches.
Technical stack
FairMatch is built with a modern, decoupled stack designed for scalability:Frontend
React + Vite with TypeScript and Tailwind CSS
Backend
FastAPI with LangChain and Google Gemini AI
Database
Supabase (PostgreSQL) with real-time sync
FairMatch is production-ready with bcrypt password hashing, full API documentation, and instant evaluation results.