Every vendor now sells AI, and most proposals arrive with a product attached. What leadership needs first is an independent view: which problems AI can solve well, what it will cost to run, and what has to be true of your data and systems before it works.
Senior consultants who have built and run AI in production, giving advice you can act on and take to a board.
Recommendations follow the problem, including when the answer is not AI.
Advice from people who deliver AI into production.
Value, cost, risk, data and architecture in one view.
Your data is not used to train public models, and access follows your permissions.
Each piece of work is scoped to a decision you need to make, and ends with a written recommendation.
Processes reviewed for where AI can remove effort, improve decisions or open revenue, ranked by value and feasibility.
Includes the ideas we recommend you drop.
A shortlist worth funding.
Benefit, build cost and running cost per use case, with assumptions stated so finance can challenge them.
Running cost is the line most AI business cases leave out.
A case finance can sign.
Model providers, cloud AI services, copilots in the products you own, and specialist vendors compared against your requirements.
We say when the feature you already pay for is enough.
A choice made on fit, not marketing.
Proposed or existing AI solutions reviewed for security, data flow, scalability, cost and supportability.
Problems found on paper are cheaper than problems found in production.
A design you can defend.
An independent review of an AI proposal, pilot or vendor contract before you commit.
Short, focused, and written for decision makers.
Confidence before signature.
Workshops for executives and boards on what AI can do for the business, the risks, and the decisions they will be asked to make.
Plain language, specific to your sector.
A leadership team aligned on the next step.
How a consulting engagement runs
Typical consulting engagements and what each one answers.
| Engagement | Question answered | Output | Model |
|---|---|---|---|
| Opportunity assessment | Where should we use AI? | Ranked use cases | Fixed scope |
| Business case | Is it worth it? | Costed case per use case | Fixed scope |
| Vendor selection | Which platform? | Comparison and recommendation | Fixed scope |
| Architecture review | Will this work in production? | Findings and fixes | Fixed scope |
| Advisory retainer | Ongoing questions | Access to senior advisors | Retainer |
Plenty of problems presented as AI problems are data quality, process or integration problems. Solving them with a model adds cost and risk without fixing the cause.
We say so when that is the case, and recommend the simpler fix. When AI is the right answer, we say exactly what it will take to make it work.
Book an AI consultationFixed-scope engagements are quoted after the first conversation.
It depends on the number of processes and systems in scope. A focused assessment of one function is short; an enterprise-wide one is longer. We quote after the first conversation.
Only if they fit. The recommendation stands on its own, and the deliverables are written so any team can act on them.
Yes. A second opinion on an AI proposal or contract is one of the most common pieces of work we do.
For an accurate assessment, read access to samples of the relevant data is useful. It is handled under your security policies and NDA.
Then we can review it against what has been delivered, and help with the parts that have stalled.
Tell us the decision in front of you. The first conversation is free and specific.