Proof of work — patterns

Systems we can point to.

These patterns show how we approach production AI: agent behavior, retrieval quality, gateway controls, governance, audit evidence, and operational handoff. The same evidence goes into every Approval Evidence Pack.

P-01 · Agent behavior and cost

Agent Evaluation & Tracing Harness

A pattern for scoring agent behavior before and after every change: task success, tool-call accuracy, regression cases from real transcripts, and per-task tracing with cost attribution.

Task success and tool-call accuracy scoring
Incidents converted into regression cases
Per-task tracing and cost attribution
P-02 · RAG and GraphRAG quality

Retrieval Evaluation Harness

A pattern for measuring answer faithfulness, source coverage, citation quality, and retrieval drift.

Faithfulness and coverage checks
Regression suites for retrieval changes
RAG vs GraphRAG decision evidence
P-03 · Policy and routing

Secure AI Gateway Pattern

A LiteLLM-style control layer for provider routing, budgets, audit logs, tenant policies, and fallbacks.

Provider routing and fallback
Budget and tenant-level controls
Audit logs for model access
P-04 · Compliance readiness

Governance Control Map

A practical map from AI use cases to technical controls, human oversight, records, and counsel review points.

ISO and regulatory alignment
Human oversight and escalation points
Evidence requirements for audit review

Proof, not product theater.

Bring an idea, a pilot, or a launch plan. We will map what stands between you and production, then scope the engagement that closes the gap, from a fixed review to a full end-to-end build.