Services
Four practices, one team. Most engagements draw on two or three of them at once, which is the point of not splitting the work across agencies.
Products and workflows built on frontier models: agents that act, assistants that know your data, and automation that runs unattended.
6 services
The layer underneath: trustworthy pipelines, predictive models, and the evaluation and observability that keep AI honest in production.
3 services
The software around the intelligence: web apps, mobile apps, and multi-tenant platforms built to be maintained, not just launched.
3 services
Strategy, architecture reviews, and honest second opinions for teams making decisions that are expensive to reverse.
1 service
How we work
Every engagement follows the same shape. You always know what week you're in, what you're getting at the end of it, and what it will cost to continue.
01 · Week 1
We start with the problem, not the technology. A working session to understand the process, the data behind it, and what a good outcome is worth. Then an honest read on whether AI is the right tool at all.
02 · Weeks 2–4
The riskiest assumption gets tested first. We build a narrow, working slice against your real data and put it in front of the people who will use it, so we learn from behaviour rather than opinions.
03 · Weeks 4–12
The prototype becomes a system: proper error handling, access control, tests, observability, and CI/CD. We ship in increments you can use, with a demo every week rather than a reveal at the end.
04 · Ongoing
Software that touches models drifts. We keep the evaluation suite running, watch quality and cost in production, and iterate on what the traces show. Or we hand the whole thing to your team, fully documented.
Ways to work together
Every engagement starts with a discovery call, and we quote after it, because a fixed price attached to an unscoped problem helps nobody.
1–2 weeks
Teams with a shortlist of ideas who need an honest read on which are worth building, and what they will actually cost to run.
4–12 weeks
A defined problem that needs to become a working system: a first AI feature, an agent, a retrieval layer, or a model in production.
Monthly, rolling
Ongoing capacity alongside your own engineers, running what we built, extending it, and levelling up the team as we go.
Next step
Tell us what the process looks like today. We'll tell you honestly whether AI is the right tool, what it would take to build, and roughly what it would cost to run.
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