Kira Project: a tamper-evident evidence layer for AI agents
Kira Project's tamper-evident evidence architecture separates AI agent logs from reports, cryptographically proving what happened and what didn't.
The Kira Project introduces a two-layer, cryptographically bound evidence architecture for a local AI pipeline. A single 9-billion-parameter model handles every stage — routing, tool use, synthesis — on an Apple M4 Pro, entirely offline.
The design separates an immutable, hash-chained execution log (Layer 1) from a human-readable reasoning report (Layer 2); the latter carries a cryptographic fingerprint of the former, so the summary can never silently drift from the record. Operator and export renderings derive from the same core, preserving provenance even through redaction.
Most notably, the system records not just what it did but what it couldn't see: unsupported claims, degraded sources used anyway, and security-relevant events like declined actions or attempted redirections are sealed into the same tamper-evident chain. It's a shift from logging agent behavior to proving it.