← All solutionsSolution · Retrieval and evals
Stop your AI being confidently wrong
Retrieval tuned on your own content and scoped per user, grounding checks on what the model claims, and an eval set built from your real failures that runs in CI. When someone changes a prompt, a test fails before a customer notices.
Who it is for
Assistants and search features that give wrong answers nobody can explain, and teams afraid to touch the prompt.
What we can build for you
Six things we can put in your product, each backed by work we have already shipped.
The four tests, for this
Where this kind of feature usually breaks, and what passing each test looks like.
Closest track: Fix retrieval, add evals
How the two weeks go
€6,000, fixed. Written findings on day five; stop there and pay half. You keep everything either way.
- Days 1 to 4Instrument retrieval: what was fetched, used and missing. Build an eval set from your own failures.
- Day 5Findings: failure rates by type, and whether the cause is retrieval, the prompt or the data.
- Days 6 to 9Fix retrieval with measured thresholds and per-user scoping, and gate the build on the evals.
- Day 10Handover: evals in CI, so the next change is a measurement, not a vibe.
Where we have done it
Tell us what you are building.
Thirty minutes, no deck. You get a straight answer about whether we are the right people, and we say no when we are not.