Versioned Decision Context and Observability

Track exactly which policies, prompts, and artifacts informed each AI decision using commit-linked context.

Capture inputs, outputs, confidence, and execution metadata as immutable decision traces designed for audit and debugging.

Re-run historical decisions in strict, tolerant, or validation modes to investigate regressions and verify behavior.

Route low-confidence outcomes to human review while allowing high-confidence paths to continue automatically.

Build evidence-ready AI workflows with traceable lineage, reproducible outcomes, and API-accessible audit records.

Integrate with existing services using Python, Node, WASM, or HTTP APIs without re-platforming your current architecture.