● Audit

AI Production Readiness Audit.

A technical assessment of your AI system across model control, prompt ops, guardrails, budget limits, tool governance, observability, and evals.

Request a Readiness Audit → Take the Scorecard

§01

When teams bring us in.

If you are moving from prototype to production, adding external tools, or exposing AI to more users, this is the fastest way to find the risk before it compounds. We review how the system is built, where it can fail, and what needs to change first. Most teams do not need more AI ideas — they need a clear view of whether the system can survive model changes, tool drift, live traffic, cost spikes, and compliance pressure.

§02

What we review

01 System architecture, identity, tenancy, and data boundaries
02 Model access, provider setup, and fallback paths
03 Prompt management and release process
04 MCP integrations, APIs, scripts, and tool permissions
05 Guardrails for inputs, outputs, and tool actions
06 Budget controls, rate limits, and kill switches
07 Tracing, logging, metrics, and error visibility
08 Eval coverage before and after release

§03

What you get

01 Seven-layer production scorecard
02 Risk register with severity, owner, and suggested fix
03 30, 60, and 90 day hardening roadmap
04 Reference architecture recommendations
05 Executive summary and technical appendix

§04

Good fit for

01 Pre-launch or beta reviews
02 Systems moving from single-user to multi-user
03 Teams adding MCPs or external tools
04 Customer-facing AI features
05 Sensitive or regulated workloads

Know where the risk is before you scale.

Get a technical baseline across the seven layers and a hardening plan your team can use immediately.

Request a Readiness Audit →