Part of the DEPLOY Method — Diagnose phase
You've spent somewhere between €50k and €500k on AI tools, pilots, and vendor contracts over the past eighteen months. You cannot tell me — with numbers — whether any of it is working. That's not a failure of discipline; it's what happens when the technology moves faster than the operating model you built to govern it. This is the DIAGNOSE phase of the DEPLOY Method, compressed into two weeks and priced as a flat fee so there is no meter running while you decide. I've audited more than 30 AI startups as a Berkeley SkyDeck advisor and shipped eight AI ventures of my own to production. The failure patterns repeat. I know what to look for, and I know which gaps are blockers versus which ones you can live with until next year.
You've bought tools but cannot prove ROI. There's a Copilot license for every engineer, an LLM API bill that grew 40% last quarter, a vendor contract for a GenAI platform nobody opens, and a chatbot that answers 200 customer questions a day. None of that is tied to a measurable business outcome. When the CFO asks whether AI is paying for itself, you genuinely do not know — and neither does your head of data.
Leadership cannot distinguish blockers from tolerable gaps. Your team brings you a list of 40 things that are 'AI risks.' Some of them are real procurement blockers — missing data lineage for regulated workloads, no evaluation harness, no incident response path for model failures. Some of them are magazine-article risks that will not matter for two years. You need someone outside the team to rank them, and your team cannot rank themselves honestly.
Nobody inside can audit the vendors. Your AI vendors demo well. They show you an eval they designed. They answer questions with the confidence of people who know your team will not check the math. You do not have an internal expert who can read a model card, stress-test a sales demo, or tell you whether the 'fine-tuning' in the contract is real fine-tuning or a system prompt. That asymmetry is costing you on every renewal.
The 90-day roadmap resets every quarter. Every three months a new model ships, a new vendor emails your CAIO, and your plan is rewritten to accommodate the latest thing. The plan has no hierarchy — no 'here is what we do regardless of what OpenAI ships next Tuesday.' Without that spine, the roadmap is reactive, and reactive roadmaps are how organizations spend three years on AI without compounding any advantage.
This is a flat-fee engagement with a fixed scope and a fixed deadline. Week one is discovery and technical assessment. Week two is synthesis and the written deliverable. I work asynchronously between interviews so your team is not blocked waiting on me.
Structured 60-minute interviews with the CEO, CFO, CAIO or head of data, head of engineering, and two operators who actually use the AI tools daily. I ask the same questions each time so I can triangulate where the narrative breaks. I also review your last four board decks for AI, every vendor contract over €25k, and your current AI policy document if one exists. By end of day three I have a working thesis about where you actually are.
I go deep on the AI systems in production or piloted — data pipelines, evaluation practice (or the absence of one), model governance, security posture, vendor lock-in, incident response. For each system I answer three questions: is it working, is it measurable, and is it defensible in a procurement review or an audit. This is the layer most internal teams cannot produce honestly because their incentives run the other way.
I rank every gap on a four-tier scale: procurement blocker (fix now, you will lose deals or fail an audit without it), ROI blocker (fix this quarter, you cannot prove value without it), scaling risk (fix before you double AI spend), and polish (fix when capacity allows). Every item gets an effort estimate and an owner suggestion. This ranking is what leadership actually needs — the full list without the ranking is paralysis.
I write the 90-day roadmap — specific projects, specific owners, specific success metrics, sequenced so early wins fund later work. Then I deliver the report to your leadership team in a 90-minute readout and handle the hard questions in real time. You leave the room with a document the CFO can defend, the CAIO can execute, and the board can review next quarter.
CEOs at SMEs and mid-market companies who have spent €50k-€500k on AI tooling over the past eighteen months without a clear ROI picture. CAIOs preparing a Q3 or Q4 commitment who need an outside assessment before they sign the next vendor contract. Public sector leaders facing a procurement review or an audit and who cannot answer the question 'is this working' with data. This is not for enterprises with AI budgets over €5M — those organizations need the 4-week Strategy Sprint with a full business case and 12-month execution plan. It's also not for pre-revenue startups who have no AI deployed yet; the audit assumes something to audit.
Because the value of an audit is the ranking, not the hours. A time-and-materials engagement creates the wrong incentive — spend more time, find more problems. A flat fee with a fixed scope means I deliver the report on day fourteen regardless of how many interviews I run, and my incentive is to get you the most useful ranking in the time available. If it takes me three extra days to finish the technical assessment, that's my problem, not yours.
Because your head of data is inside the political economy of the decisions being audited. They cannot tell you that the vendor contract their team signed last year was a mistake — not because they'd lie, but because the incentives do not support that conversation. An outside auditor with no stake in the history can rank gaps honestly. I also bring pattern recognition from 30+ other audits that your head of data, by definition, does not have.
Scope, price, and who does the work. A big-four AI assessment is typically 8-12 weeks, €200k+, and the work is done by analysts with less AI production experience than your own engineering team. This is two weeks, flat fee, and done by someone who has shipped eight AI ventures to production and audited thirty more. The deliverable is sharper because the judgment is sharper, and you get a document your CAIO respects rather than one they have to re-do internally.
Then that's what the report will say, and it will say it in writing with evidence. About one in five audits concludes that the organization is investing ahead of its operational capacity and should consolidate before adding more. That is a legitimate and often expensive finding — a €300k vendor contract not renewed pays for the audit twenty times over. I do not have an incentive to sell you more AI; I have an incentive to give you a ranking you can defend.
Let's discuss how this service can address your specific challenges and drive real results.