What Is AI Evidence Infrastructure?
AI evidence infrastructure preserves the information required to reconstruct, inspect and verify how an AI-assisted process moved from source material to an outcome.
Read technical note →Research / Technical Notes
Verification, evidence and AI infrastructure.
Technical notes on reconstructability, provenance, verification boundaries and evidence-aware AI systems.
Why AI Audit Logs Are Not Enough
Audit logs can show that an event occurred. Verification requires enough evidence to reconstruct what happened, which inputs were available, what changed and under which system state.
Read technical note →Provenance, Traceability and Verification: What’s the Difference?
Provenance, traceability and verification are related but distinct. Together they form a stronger evidence model for reconstructing and independently reviewing AI-assisted workflows.
Read technical note →What Is a Verification Boundary?
A verification boundary defines which identities, inputs, state, transformations and claims are actually covered by a verification result.
Read technical note →From Evidence to Decision: Where Meaning Can Change
Information can remain technically intact while meaning changes across summaries, transformations, AI analysis and decision records. This article examines where those shifts occur and how to make them inspectable.
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