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Every candidate claim traces back to a source.

The evidence engine links claims to resume pages, snippets, parser confidence, scorecard versions, and reviewer actions.

DPA supportSSO / SCIMAudit exportsNo model training by default
ClaimLed platform team of 5 engineers94% confidence
Sourceresume.pdf · p.2led 5 engineers
DecisionShortlist reviewedScorecard v3.1
Product proof

Every score includes its evidence.

CVault’s visual grammar is built around source chips, page references, confidence markers, audit rails, and evidence export packages.

  • Source-aware scoring
  • Page-level provenance
  • Confidence you can trust
  • Audit-ready by design
resume.pdf · p.2Claim highlighted

Owned delivery for a real-time payments platform and led 5 engineers across backend services. Designed APIs for transaction ingestion, monitoring, and customer-facing reliability.

Page 2 of 6Parser v4.2.1Scorecard v3.7
resume.pdf · p.2Platform leadership94%confidence
resume.pdf · p.3AWS production depth95%confidence
portfolio.pdf · p.7Distributed systems92%confidence
{
  "candidate_id": "cand_789",
  "role_id": "role_123",
  "role_fit": 0.94,
  "parser_confidence": 0.98,
  "evidence_points": 28,
  "review_state": "in_review",
  "ats_status": "synced"
}
Evidence scoring

Generic AI scoring versus CVault evidence scoring.

The difference is not prettier summarization. The difference is traceability.

Generic AI scoring

Produces a confident summary, but hides the source path, confidence, reviewer state, and exportable audit evidence.

CVault evidence scoring

Preserves page references, document snippets, parser version, scorecard criteria, reviewer actions, and ATS handoff state.

Private pilot

Run one sample role through CVault.

Use permitted resumes, one live role, private workspace controls, and exportable evidence before a wider rollout.

Run a sample roleTalk to sales