Summary

CVMatch matches candidate CVs to role descriptions using minimal infrastructure and pragmatic AI. Focus: signal over noise, reproducibility, and low operational overhead.

Problem

People waste time on manually checking if their CV matches job descriptions or are busy copying and pasting from/their AI chat. LinkedIn’s “AI” tool, thought to be a great promise, is cumbersome and not a good fit.

Approach

  • Embedding-based similarity for CVs ↔ role text.
  • Lightweight prompt ranking with guardrails.
  • Deterministic pipelines, versioned artifacts.
  • Privacy first.
  • Strict token budget management to reduce costs.
  • BYOA - Bring Your Own AI

Architecture

  • Ingestion: parse PDFs/Docs to normalized text.
  • Vectorization: embeddings store.
  • Scoring: hybrid rank (semantic + keyword boosts).
  • Review UI: simple shortlist with rationales.

MLOps

  • Reproducible runs (seeded).
  • Config-as-code (YAML).
  • Eval set and regression checks.
  • CI for lint + smoke tests.

Results

  • Faster shortlist creation.
  • Clear rationales for ranking.
  • Easy to extend with domain rules.

Try It

Install CVMatch directly from the Chrome Web Store:
👉 CVMatch on Chrome Web Store