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AI Production-Readiness Audit & Buildout

The problem

A promising LLM or agentic prototype works in a notebook and stalls before production. No deployment path, no evals, no guardrails, no cost ceiling, and no one who owns it on call. The model was never the hard part — the infrastructure, governance, and operational ownership are.

The approach

A fixed-scope audit of the stalled system against a production-readiness bar — deployment, evaluation, observability, guardrails, cost, and ownership — followed by a scoped buildout that closes the gaps. Senior-only delivery, machine-verified, with a mandatory production-safety gate before anything ships.

Engagement

Fixed-scope audit first (1–2 weeks), then a scoped implementation statement of work. The audit stands alone — you can take the findings and run.

What's delivered

  • Production-readiness assessment scored against a concrete rubric, with prioritized risk register
  • Deployment pipeline: reproducible, gated, rollback-safe (no click-ops, no long-lived keys)
  • Evaluation harness + observability so regressions are caught before users are
  • Guardrails: input/output controls, policy-as-code, human-in-the-loop where it matters
  • Cost controls: budgets, per-feature spend visibility, and a ceiling that pages before it bankrupts
  • A written ownership model: who runs this, what they watch, what wakes them up

The outcome

A previously stalled system in production with a named owner, a defensible safety story, and a spend curve that finance signed off on.

Think this is your situation?

Request an audit. You'll hear back from the person who'd do the work.

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