AI Production Readiness Audit
A short, fixed-scope review of whether your AI system is actually ready for production — or still a demo — with a prioritized, honest action plan for the gap. The fastest way to know what stands between you and dependable production.
What it covers
I review your AI system across the dimensions that decide whether it survives production:
- Success criteria — is there a defined task, bar, and sign-off, or is "good" a feeling?
- Evaluation — can you prove pass/fail against the bar on real data?
- Grounding & data — retrieval quality, data readiness, and where bad answers come from.
- Cost & latency — what it costs at real volume, and the levers to control it.
- Security — prompt injection, data exposure, agent permissions, sandboxing.
- Reliability & ownership — observability, drift, and whether a named owner can run it.
What you get
- A prioritized findings report — what's production-ready, what's not, and what's highest-risk.
- A concrete, sequenced action plan to close the gap.
- A clear read on whether you're ready to ship, close to it, or still at the demo stage.
Pricing is shown up front on Topmate. Prefer to self-check first? The free 10-question assessment gives you a quick score in two minutes.
How it works
The audit is deliberately lightweight on your side. You share what exists — the system, a few representative examples of real inputs and outputs, and whatever evaluation or monitoring you have (including "none"; that's a finding, not a failure). I review it asynchronously against the dimensions above, then we walk through the findings together in a working session where you can push back, add context, and decide what actually gets prioritized. You end the week knowing exactly where you stand and what to do next — whether or not we ever work together again.
Who it's for
Teams about to put an AI system in front of customers, a regulator, or a security review — and anyone whose promising pilot keeps stalling before launch. Grounded in real production delivery across FinTech, Open Banking, telecom, energy, and critical national infrastructure — see the case studies.
What colleagues and clients say
“Together, we undertook a strategic cloud cost optimization and financial governance program that resulted in a significant reduction in overall BigQuery warehouse costs. […] What stands out about Pratik is his ability to work as a true partner.”— Ashish Chandra, Head of Data Engineering at Tata Steel, from my LinkedIn recommendations
“Pratik brings a combination of clean architecture, thoughtful concurrency patterns, and genuine attention to code quality that elevates every project he touches. He approaches problems methodically [and] writes production-grade code that's maintainable long-term.”— Ruby Kaushik, Staff Software Engineer at Infoblox, from my LinkedIn recommendations