I built an AI résumé tool that refuses to lie about your experience

Most AI résumé tools have the same flaw: they hallucinate. Ask them to tailor your résumé for a job requiring "Rust experience" and they'll happily invent a Rust project you never worked on. It reads great — until the technical interview.

I wanted the opposite. So I built Citevault: a local-first résumé tailoring tool where every claim is either grounded in your own evidence, or refused and flagged as a gap.

No fabrication. No API keys. Runs entirely on your laptop. (Model weights are pulled from Hugging Face once on first boot; after that, no outbound connections.)

The core idea: claim-level grounding

Every bullet in your résumé starts as a claim. Citevault processes each one through a pipeline:

1. 
   Retrieve — hybrid BM25 + dense embedding search over your indexed evidence (master résumé, project READMEs, blog posts, anything you upload)


2. 
   Re-rank — BGE cross-encoder scores the top candidates for relevance


3. 
   Verify — Gemma 4 reads the claim alongside the retrieved span and gives a verdict: SUPPORTS, PARTIAL, UNCLEAR, or CONTRADICTS
   


4. 
   Rewrite or refuse — SUPPORTS → the claim is verified and cited; PARTIAL → rewritten to match only what the evidence actually says; UNCLEAR → a rewrite is attempted, and if it still can't be grounded, refused and gap-reported; CONTRADICTS → refused immediately and gap-reported

in the repo.

The code is on GitHub: github.com/jaberoma/citevault — MIT licensed, no account required, runs on any laptop with Docker.

Citevault's contract is simple: every claim in your résumé either links to a source span in your own evidence, or it does not appear. No exceptions.