Ship AI you can actually trust.
We build AI that does real work for you — a team of them, splitting a job up and checking each other. Then we prove it is working, in plain numbers, every week.
Working with teams worldwide
You ask for one thing
“Plan me a weekend in Lisbon for under €400.”
A team of AI splits up the work
- ResearcherdoneFinds the flights, places to stay, things to do
- BudgeterdonePrices it all up and keeps it under €400
- PlannerworkingPuts it in an order that actually works
Then it stops and waits for you
Nothing gets booked, sent or paid for until you say yes. That approval step is the difference between AI that helps and AI you have to clean up after.
Recently shipped — all of these are live
See the rest →
Two things, in this order
The AI work is what we are known for. The engineering team builds the actual product it lives inside — because an AI feature on its own is not something your customers can use.
AI & Automation
A score, not a shrug
Ask most teams whether their AI is working and you get a shrug and an anecdote. We set up a standing test — hundreds of real questions, run automatically every time anything changes. If quality slips, the release stops before your customers see it.
For engineers: show the scores and CI output
- Finds the right information96%
- Answers stay true to the source94%
- Uses your systems correctly99%
- Says “I don’t know” when it should88%
- Resists being tricked92%
$ npx devmations-evals run --suite support-agent ✓ retrieval relevance 230/240 ✓ answer faithfulness 226/240 ✓ tool call validity 178/180 ! refusal handling 84/96 ✓ injection resistance 110/120 94.2% overall · threshold 90% · PASS regression vs main: noneA customer asks
“Can I still return this? I ordered it 40 days ago.”
Yes — our returns window is 60 days, so you are still covered.
Made up. Your policy says 30 days. Now you either honour it or argue with a customer.
Our returns window is 30 days, so that order is just outside it. I can pass this to the team to look at as an exception.
Taken from your actual returns policy. And when it is unsure, it says so instead of guessing.
What actually happens
What one request looks like, start to finish
- 1
Someone asks
A customer or a colleague asks a question, in their own words.
- 2
It finds the facts
It searches your documents and systems for the parts that actually answer it.
- 3
It works out the answer
Using what it found — not what it half-remembers from the internet.
- 4
It does the job
Replies, looks up an order, books the thing. Whatever you asked it to handle.
Then we check it
Every answer is scored against what a correct answer looks like. This is the step almost everyone skips.
And what we learn goes straight back in. That loop is why the system gets better every week instead of quietly getting worse — and it is the difference between AI you can rely on and AI you have to keep apologising for.
Four commitments
Measure before you build
We start by turning where you are now into a number. Without that, "better" is just an opinion, and nobody can tell whether the money was well spent.
Nothing ships unchecked
Quality checks run automatically from the first week, and a change that makes things worse cannot go live. A standard nobody enforces is a wish, not a standard.
You are not stuck with us
Documentation and instructions are part of what we deliver. If you want to bring the work in-house next year, that should be a decision, not a project.
We tell you what we do not know
You will hear which numbers we measured and which we estimated, and what would change our advice. Sounding certain is easy; it is also how projects go wrong quietly.
Things we actually shipped
Every project below is a live deployment you can open.
For the technical reader — what we build with
- OpenAI
- Anthropic Claude
- LangChain
- Model Context Protocol
- Playwright
- Pinecone
- pgvector
- Next.js
- React Native
- PostgreSQL
- AWS
- GitHub Actions
Before you get in touch
- What does DevMations do?
- DevMations is an AI engineering agency. We build AI assistants and agents that work with your own data, the testing that proves they behave correctly, automated quality checks for software generally, and secure connections between AI tools and your internal systems. We also build the web and mobile products all of that lives inside.
- How do you engage with clients?
- Most start small: we review what you already have — the AI, the tests, or the codebase — and give you a written answer on what is wrong and what we would do about it. From there you can have us build it, or take the plan to your own team. There is no long contract to get started.
- Do you work with teams that already have AI in production?
- Yes — that is the most common reason people call. Something works in a demo and behaves unpredictably once real customers use it. We start by measuring what it is actually doing, which makes everything after that a lot cheaper to fix.
- How do we work together across time zones?
- We work with clients worldwide, with hours that overlap the European and North American mornings. Written updates are the default rather than standing calls, so progress is visible without needing everyone in a room at the same time.
Have an AI system you cannot vouch for?
Tell us what it does and where it goes wrong. We will tell you whether the problem is retrieval, prompting, tooling or something else — before you spend anything.
Book a call