Structured Review
Interactions are evaluated against controlled review criteria designed for sensitive information handling, disclosure conditions, privilege considerations, and citation reliability.
Evidence that survives beyond the AI session.
AI systems are becoming part of the permanent record. Most organizations still cannot reliably explain what happened inside them.
Persistent History
Review outcomes remain tied to timestamps, attribution metadata, policy lineage, and supporting artifacts designed for long term legal, compliance, and organizational review.
Distributed Environments
Activity can be processed across MCPs, APIs, uploads, generated files, review chains, and downstream systems without requiring organizations to centralize workflows into a single platform.
AI legal risk discovery and evidence system
Reconstructable
by design
Independently timestamped
Evidence records verified through trusted external timestamp authorities.
Reproducible findings
Identical inputs and policy versions produce consistent review outcomes.
Distributed review systems
Processes activity across MCPs, APIs, uploads, generated filings, review chains, and downstream systems.
The AI session disappears.
The consequences usually do not.As AI becomes embedded across documents, filings, reviews, and internal systems, organizations increasingly need reliable ways to understand what happened inside those interactions after the fact.