CandiSift vs Jarvi

CandiSift is an open-source applicant tracking system for parsing resumes, matching candidates to job descriptions, and ranking applicants through a bias-audit workflow. Recruiters can create roles, upload PDF, DOCX, or plain-text resumes in batches, and review ranked results with accept or reject decisions. The screening sequence strips personally identifiable information, applies hard filters, ranks candidates, then sends those who remain to persona agents and human review. Token-cosine ranking, technical and risk personas, and synthesis contribute to that process. Before confirming a staged batch, users can view estimated processing costs; deterministic filters run before the paid LLM stage. CandiSift connects to Anthropic Claude through Agno persona agents, with an offline stub LLM available when there is no API key. It can run in Docker, uses SQLite by default, and supports a Postgres database URL. The project describes HTTP Basic authentication, security headers, rate limiting, upload validation, request limits, prompt-injection defenses, and an append-only audit log. The API includes a bias-audit endpoint. The project has no shipped accuracy benchmark; OCR, embeddings/FAISS, and skillNER are described as swaps rather than included defaults. The software fee is $0.00 per free; LLM processing may incur per-token costs.

Jarvi has no write-up on Specifiction yet; its figures are above.