SitRep · before you build

Find the defects your AI would repeat.

Inspect the source collection for duplicates, contradictions, stale versions, and structural weaknesses before those problems become confident AI answers.

SitRep · before you build product mark
01

What SitRep returns

A completed SitRep run produces a sealed data-audit package reflecting the checks actually selected and the scope actually examined.

  • Bound Data Audit Report and leadership Executive Summary
  • Audit Scope, Data Card, and Methodology records
  • Findings report covering census defects, unsupported or contradicted claims, conflicts, gaps, and referrals as applicable
  • Suggested Corrections and prioritized Gap Remediation
  • Framework Crosswalk and Annex IV Data Record
  • Isolation Posture and Audit Dossier
  • Machine-readable findings, evidence JSON, data-card YAML, SARIF findings, and OpenTelemetry spans
  • Canonical results, configuration, logs, signed manifest, integrity checker, and hash-bound reviewer trail
02

Source readiness before model evaluation

SitRep answers the question that comes first: whether the underlying material is coherent enough to support a trustworthy assistant.

  • Duplicate and near-duplicate records
  • Conflicting statements and competing versions
  • Stale or superseded material
  • Coverage and structural weaknesses
  • Decision-ready summary for remediation planning
03

One lifecycle, separate decisions

SitRep assesses the source material. Scout assesses the AI’s answers. Watchtower assesses deployed behavior over time. Keeping those scopes distinct makes the evidence easier to defend.

04

Reports for action

The output translates corpus-level findings into a concise management view without discarding the underlying machine-readable evidence.

Next step

Test the claim on your own system.

Plan a guided pilot