Service · Products
Apps and services with AI inside
Sometimes the answer is not an agent bolted onto what you have, but a product built around the thing you actually do. We build those end to end.
What usually goes wrong
- The AI feature is added last, so it feels stapled on and nobody uses it.
- There is no way to tell whether a change made the product better or worse.
- It works for ten users and falls over at a thousand, because nothing was measured.
What we build
- Web and mobile products, and the backend underneath, as one piece rather than three vendors.
- LLM features designed into the flow instead of parked behind a chat button.
- Evaluation and observability from the first version, so quality is a number you can watch.
- A deployment pipeline with a quality gate, because shipping should not be the risky part.
How we build it
TypeScript across the stack where it fits, Postgres for data that matters, and cloud infrastructure your team can actually operate. We favour boring, well-understood choices for everything that is not the interesting part.
We put AI in almost any business.
- 01
Discovery
We map your processes and data to find where the lost time lives.
- 02
Advisory
We identify what can be automated and what AI actually improves. Judgment, not hype.
- 03
Proposal
We tell you what to do and how, with clear scope, ROI and risks.
- 04
Adoption
We build the agents and integrate them into what you already use.
- 05
Ongoing support
We measure, tune and stay with you as you use it.
Questions we get asked
Do you only build with AI?
No. Plenty of what we ship has no model in it at all. Putting AI where it does not belong is a good way to make software worse.
What do I get at the end?
The product, the source, the infrastructure definition and the documentation. Nothing runs on a machine only we can reach.
Can you take over an existing project?
Often yes. We start by reading it and telling you honestly what we found, which is a short engagement in itself.
What are you trying to build?
Describe it in your own words. The discovery stage exists precisely so nobody commits to a scope before understanding the problem.