Every candidate claim traces back to a source.
The evidence engine links claims to resume pages, snippets, parser confidence, scorecard versions, and reviewer actions.
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
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.
{
"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"
}Generic AI scoring versus CVault evidence scoring.
The difference is not prettier summarization. The difference is traceability.
Produces a confident summary, but hides the source path, confidence, reviewer state, and exportable audit evidence.
Preserves page references, document snippets, parser version, scorecard criteria, reviewer actions, and ATS handoff state.
Run one sample role through CVault.
Use permitted resumes, one live role, private workspace controls, and exportable evidence before a wider rollout.