The board has asked for an AI plan, three vendors have pitched three platforms, and nobody can name the first use case with a number next to it. Meanwhile the data those pitches assume lives in four systems and someone's inbox.
We spend time with the people doing the work and look at the real data before ranking anything. You get a short list: value, risk, what has to be fixed first, and what it costs to run each month. Some items get a clear no, because the problem is a rule or a hire, not a model.
What we offer
- Use-case triage
- Data and workflow audit
- Running-cost model
- First-year roadmap
How we work
- 01Talk to the people who do the work
- 02Inventory data, tools and handoffs
- 03Rank by value, risk and effort
- 04Cost each one in production
- 05Roadmap, in writing
Offers
- AI Sprint: One process, two weeks, a measured result.
Also in AI
- AI Integration: Language models inside the product you already have, with guardrails and evals.
- AI Automation & Agents: Repetitive work done by software, with people where it matters.
- Data & Custom ML: Trained models and optimisers for the problems a prompt cannot solve.
Ready to talk?
