The AI Decision Audit
Make the right AI call.Prove it before you commit.
Your leadership keeps circling three questions: where does AI create real value in our business, what is it worth, and how do we run it confidently?
The Audit settles all three, decided and de-risked, and proves the top use case with a working demo on your own data, edited by your own team. Strategy and engineering in one room, on your business, not a generic playbook.
Senior strategists and engineers on your AI strategy
Backgrounds across McKinsey, EY, and Feedzai. Operators who have shipped production AI, not just advised.
Book your AI Decision Audit.
Senior strategists and engineers, on your business. Not a generic playbook.
Most AI strategy ends in a slide deck, then dies in a pilot that never ships.
The cost is rarely just a wasted quarter: it is a year of lost ground, a budget you cannot re-spend, and a board that stops backing your next call.
The AI Decision Audit ends somewhere else. The decisions that shape your next decade, answered with evidence:
Backing the wrong use case first costs a year and credibility. Every candidate is scored on business impact, operational readiness, and speed to value, naming where to begin and what to defer.
Unclear AI governance stalls a program in review. A clear, defensible strategy, ready for the board, auditors, and the EU AI Act.
A single data exposure or over-permissioned agent can halt the program. Data residency, retention, and least-privilege access are defined for every agent and tool call.
A strategy detached from your environment will not deploy. A path to production that fits your stack and data-residency requirements, with no lock-in to a single model or cloud.
AI that no internal team can operate fails after launch. Ownership is defined: who authors the agents, who operates them, and where to build capability versus hire.
AI spend escalates while returns stay unquantified. A cost and value model in your own numbers, predictable at scale and defensible to the board.
Scored against the Production AI Decision Framework: twelve evidence-gated dimensions across Ownership, Trust, and Leverage.
You don't leave with a plan to evaluate. You leave with the decision made, de-risked, and the evidence to defend it.
We stand behind that: leave with the decision and a working demo on your own data, or you do not pay.
Not a score. Not a hand-off. A decision, proven.
It is not
- A maturity score that tells you what you already feel
- A strategy deck you are left to build alone
- A canned product demo, dressed up as advice
It is
- The right call, de-risked at every layer
- A working demo, hands-on with your team
- A board-ready case and roadmap, owned by you
Six deliverables. Yours to keep, built to compound.
Leadership education brief
Your leaders, fluent in the full AI lifecycle: governance, model sovereignty, integrations, evaluators, authoring. They lead the decision instead of being sold to.
Infrastructure decision
Where your AI runs and what you build versus buy, documented with the reasoning behind each call. A decision your engineering team can act on.
Prioritized roadmap
Every use case scored, the first to build named, the rest sequenced behind the decision gates that keep the program on track, not drifting into experiments.
Quantified business case
The value model in your own numbers: the costs, the returns, and the payback, built to defend to your finance team and the board.
Working demo, built by your team
An Interactive Agent on your number-one use case and your own data, built by your experts alongside us. The strategy proves out and the capability stays in-house.
Board reporting and scoped Pilot
Your decided strategy and the value case, presented to your board, with a Pilot already scoped to build the first use case for real.
From first conversation to board reporting.
Phase 1
Week 1
Diagnose
Leadership interviews, a review of your data, systems, and governance, and the education sessions that level the room on the full AI lifecycle.
Phase 2
Weeks 2-3
Decide and prioritize
We score every use case and de-risk each decision layer with you, from governance and security to infrastructure and economics.
Phase 3
Week 3
Prove
We build a working demo on your number-one use case and get your people hands-on with it.
Phase 4
Weeks 3-4
Board reporting, path to production
The decided strategy and the value case, presented to your board, and a Pilot scoped to build it for real.
Four weeks, fixed scope, fixed fee, agreed before we start.
A strategist and an engineer who ships, in the same room.
This is a pairing you could not hire, and would not get from a consultancy: strategists who set AI direction and the engineers who ship it, in the same room. Operators who have carried AI into regulated, high-stakes production, with backgrounds across McKinsey, EY, and Feedzai. Not advisors who hand you a deck and leave, operators who build the thing and prove it on your data. The pairing is the point: the strategy survives the board conversation because it already survived the engineering one. Your team is embedded throughout, so by the close your own people are editing the working demo and hold the operating knowledge. We run our own operation on this platform, so we hold ourselves to the standard we sell.
Who this is for.
A fit
- You carry a board-level AI mandate
- You operate in a regulated, high-stakes environment
- You want production, not another experiment
Not yet
You are exploring, with no decision to make
You want a generic score to file away
You only want to see the product
Book a demo instead
The proof is your own use case.
Most assessments end in a document. This one ends with a working demo on your highest-value use case, on your own data, inside the engagement. You see it work before you commit anything to production. That is the difference between a recommendation and a decision you can defend.
01
AI Decision Audit
Prove the call
02
Pilot
Prove the impact
03
Scale
Operating advantage
The Audit proves the right call. The Pilot proves the impact.
Common questions about the Audit
What it is, what it is not, what you own, and how it leads into the Pilot. The decision-making questions, answered directly.
The next step
Make the call. See it work.
Book your AI Decision Audit. A senior strategist and a production engineer, on your business, ending in a working demo and a call you can defend.