A generative AI feature is only useful at work if it answers from your content, shows where the answer came from, and behaves sensibly when it does not know. That is what we build.
The model is the commodity. The value is in retrieval over your documents and systems, prompts that encode how your business actually decides, evaluation that catches regressions, and an interface that makes the source obvious.
We build assistants, search and drafting tools that people keep using after the novelty wears off — because they save time and can be checked.
Part of Enterprise AI DevelopmentA focused engagement, with the parts that usually get skipped left in.
If the content is not there, it says so. That single behaviour is what earns trust.
A fixed test set and scores in the pipeline, so quality is visible rather than anecdotal.
Per-answer cost tracked from week one, with smaller models used wherever they suffice.
Short cycles, visible progress, and honest checkpoints where you decide what happens next.
Book a discovery callA real task, a named owner, and today’s time and error rate as the baseline.
Content prepared, chunked, permissioned and searchable — the part that decides quality.
Real questions, expected answers, iterate until the score holds.
Draft-and-approve first. We remove the gate only when the evidence supports it.
An agent is a loop, not a chat window: it looks at a case, plans a step, uses a real tool, then checks whether it worked.
ExplorePrediction is only worth paying for if it changes a decision.
ExploreAI and analytics inherit whatever your data is.
ExploreA model in production is a product with a lifecycle: retrained, monitored, approved and occasionally rolled back.
ExploreTell us where you are and what you need it to do. We will be straight with you about the shortest route there.