Practice 04 of 04
AI & data
Pragmatic AI that earns its keep. We've watched enough hype cycles to know which interventions move the number, and which just look good in a deck. We build the durable systems that come after the demo.
Capabilities
What this practice covers.
- ·Applied LLM systems & agents
- ·Retrieval, evals, and guardrails
- ·Internal tooling & operator copilots
- ·Data foundations for AI
- ·Risk, governance & responsible deployment
When you call us
Situations we recognize.
Most engagements start with one of these. If something on this list sounds familiar, that is usually a sign we should talk.
A first AI pilot impressed the executive team, and now nobody is sure how to scale it.
Your data is messier than the AI vendors implied it would need to be.
An operator workflow is the obvious AI candidate, but the model keeps getting it wrong.
You need a defensible point of view on AI risk for the board.
What good looks like
The work we leave behind.
AI that survives the second user. Evals you trust. A clear-eyed read on which problems AI should own, which it should support, and which it should leave alone.
Looking at this kind of work?
If a situation on this page sounds familiar, that is usually a sign we should talk. A senior practitioner will respond within two business days.