Services
Get ready for AI, then ship the first thing.
Most AI projects do not fail on the model. They fail on data nobody can reach, permissions nobody wrote down, and no agreed way to tell whether the output is any good. We fix that groundwork — and then build the first feature on top of it.
What this is
Groundwork first, then something that runs.
We start with what you actually have: where the data lives, what shape it is in, who is allowed to see it, and which of your problems a language model would genuinely help with. That produces a plan and an honest list of what is not worth doing. Then we build the first production feature on that foundation, with evaluation in place from day one so you can tell whether it is working.
Usually built with
- TypeScript
- PostgreSQL
- pgvector
- LLM APIs
- Evals
- EU AI Act
What you get
A data and access inventory
What exists, where, in what condition, and what has to be cleaned or connected before anything can use it.
A shortlist worth building
Candidate use cases scored on value and feasibility — including the ones we recommend you skip, and why.
The first feature, in production
One capability built end to end: retrieval, prompts, guardrails, and an interface your people will actually open.
Evaluation you can keep running
A test set and scoring harness, so changing a prompt or a model is a measured decision instead of a vibe.
Fit
This is probably right if…
- Leadership wants "something with AI" and nobody has scoped what that means.
- You have plenty of documents or records and no clean way to query them.
- A pilot impressed everyone in a demo and then never reached production.
- You need the EU AI Act and GDPR questions answered before you can start.
Want to talk?
Tell us what you want AI to do.
Even a rough description of the problem is enough to start. We reply within two business days, and if we think AI is the wrong tool for it we will say so.