AI reality-check
A short, fixed-scope review of where AI genuinely pays off for you, where it will burn money, and what’s actually worth building. You get a clear written assessment you can act on — whether you build it with us or not.
What we do
Practical AI, built by people who ship it.
We help teams get real value from AI — first by working out where it genuinely fits, then by building it so it can be trusted. Four ways we usually help, each scoped so you always know what you’re getting.
How we help
Four ways in.
Most engagements start small — a clear, bounded piece of work — and grow from there if it’s working well.
Build & integrate
Design and build AI into your product or workflow: retrieval over your own documents, assistants that stay grounded in real evidence, speech and audio, and the plumbing around them — cost control, rate limits, moderation and sensible fallbacks.
Rescue & audit
An AI feature that made a great demo but can’t be trusted in production, costs too much, or quietly stalled. We work out why and get it to something dependable — or tell you plainly if the approach itself needs to change.
Your AI team
For agencies and product teams with AI work but no AI depth in-house: we act as the AI engineering behind your team, so you can take the work on while we build the parts that need real experience.
How we work
Honest, collaborative, remote-first.
We’re a technical team that likes hard problems and small, motivated groups of people. We’ll tell you where AI won’t help before we build anything, and we’d rather scope something small that works than sell something big that doesn’t.
Best with open teams
Our best work is with people who want to explore and iterate — not hand over a fixed spec and disappear.
Remote-first
A face-to-face intro and setup is welcome; the work itself is remote, so you get senior attention without the overhead.
Truthful about limits
Grounded, checkable results — and a straight answer when AI is the wrong tool for the job.
Also from Jamain
Senior engineering, beyond AI.
Decades of building and maintaining business-critical software mean we can also take on the harder, non-AI engineering that surrounds a project — difficult production systems, legacy code and architecture — when it helps to have one team across the whole thing.
Start a conversation
Tell us the problem.
Describe what you’re trying to do with AI — even roughly — and we’ll tell you honestly what’s worth doing and how we’d approach it.