CVMatch
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