Artifact to Finding Ladder
Documents, transcripts, reports, and other source artifacts enter a controlled review path. Claims do not become findings until the review state permits promotion.
Deterministic verification for governed AI workflows
A verification layer for AI governance, compliance, and reliability review workflows. DVS records evidence state, review transitions, contradictions, promotions, audit events, and export boundaries before downstream artifacts are allowed to speak with certainty.
Input material with stable source identity.
Assertion extracted or entered for review.
Contradiction, supersession, and state checks.
Only promoted when support and state permit it.
Output language constrained by review state.
For AI governance and compliance platforms
Governance platforms often capture policies, risks, approvals, and reports. DVS focuses on the machine boundary underneath those workflows: what source supports a claim, what contradiction blocks it, what review state allows promotion, and what the resulting export is permitted to say.
DVS is designed to support record-keeping and traceability concerns reflected in Article 12 of Regulation (EU) 2024/1689 for high-risk AI systems. It is not a legal compliance certification and does not replace counsel, governance review, or conformity assessment.
Architecture summary
Documents, transcripts, reports, and other source artifacts enter a controlled review path. Claims do not become findings until the review state permits promotion.
Known conflicts, stale source material, blocked propagation state, and superseded artifacts can stop downstream use.
State changes are recorded, and export language is constrained so the output does not overstate certainty.
Engagement lanes
A constrained technical review of DVS against one workflow. The recommended first step is a proof-of-value pass using non-sensitive or synthetic materials, followed by an integration discussion only if the boundary is useful.
A fixed-scope document review service. You provide a bounded set of materials; the output is a source-attributed reliability packet separating supported assertions, weak claims, contradictions, unresolved gaps, and export-safe findings.
Reliability packet output
A Reliability Review packet is designed to show what each material assertion depends on: source support, contradiction state, review state, and permitted downstream language.
Academic review track
A separate de-identified research track maintains a longitudinal case model of technology-mediated conflict tracking, dyadic inversion, and AI-mediated communication structuring.
Sanitized briefs are available for academic review. Raw exports, identifying details, and private records are not sent in first contact.
Contact
Creator of DVS. Building under the UnFragged project name.