Labs
Applied AI
Evaluate what AI can do before committing a product around it.
Focused experiments for organizations that need evidence about model behavior, retrieval, agents or human-in-the-loop workflows.
Questions we can test
Model selection, retrieval quality, evaluation design, workflow fit, safety constraints and the operating cost of a proposed AI capability.
What an engagement produces
A scoped prototype, evaluation set, findings, risks and a recommendation to build, change direction or stop.
How to begin
Bring the decision you need to make, representative data and the people responsible for the real workflow.
How an engagement works
- Clarify the buyer, problem, constraints and decision.
- Define the architecture, scope, deliverables and owners.
- Build through visible review gates with risks made explicit.
- Launch, hand over and agree the operating or improvement path.
What you receive
A documented scope, the agreed working output, decision records, delivery materials and a clear route into operation or the next phase. Outcomes are described without invented percentages or unsupported proof.
Ways to engage
Focused discovery, a defined project, an embedded delivery team or a phased partnership—selected to match the uncertainty and accountability required.