Custom AI agents built for your trade
Engineer ApS builds custom AI agents for one trade: wired to your systems, tested on cases your experts write, supervised by people, never tied to one model.
Photo: monikawl999 / Pixabay 
Photo: HerrDann / Pixabay
The model is the part of an AI agent everybody talks about, and the smallest part of the work. What makes an agent useful in one trade — shipping, a clinic, a law office, a warehouse, an engineering firm — is everything around it: what it is connected to, how it is measured, who checks it, and what it may touch. We build that part, for your trade, around the model that does each job best, and we keep the model replaceable.
Connected: to the systems the work lives in
An agent that cannot reach your systems can only talk. We connect it to the ones the work happens in — the ERP, the CRM, the booking system, the mailbox, the document store — each through a described tool with a narrow job: look up a vessel, draft a quote, file a case. Tools are offered over MCP or an API, every input is typed and validated, and an agent that needs your company’s own records reads them from data made ready for it. Memory of past cases lives in your database, not in a vendor’s chat history.
Measured: against cases your experts write
Without tests, “it seems better” is the only measurement anyone has. We sit with the people who do the work and write down real cases from your trade, each with the answer a senior person would give. Every change — a prompt, a tool, a model — runs against all of them before it ships, and the score is kept per case over time, so a fix for one customer cannot quietly break another. It is the quality gate we run on our own code, applied to an agent’s answers.
Supervised: a person decides where it matters
Not every action should be the agent’s alone. We write down, with you, what it may do on its own, what it drafts for a person to approve, and what it never touches, and the rules are enforced in the tools rather than asked for in the prompt. A review screen shows a person what the agent proposes and why; a correction made there becomes a new test case. Every step is traced with OpenTelemetry, so when an answer goes wrong you can see which tool, which document and which model produced it.
The model is the part you rent — the cases, the tools and the rules are the part you own.
Build the part you own well, and every model released after today is an upgrade rather than a migration.
Better when a better model ships
Models improve every few months, and an agent tied to one of them ages with it. Ours route each job to the model that does it best — a small, fast one for sorting and extracting, a large one for judgement — and the choice is configuration, not code. When a new model ships, it runs against your cases overnight, and you switch on the score rather than on the announcement. A better model should make your agent better by morning, and that only happens when the rest of it was built to allow it.
The work behind it
The habits that make an agent trustworthy are the ones we already keep in our own engineering. We built a guard engine of 268 commit checks and a commit gate of 22 linters with no warning tier, then wrote tests for the checkers themselves so a check that reads nothing cannot report clean. We built first-party error monitoring and tracing, made six collectors state what they skipped, and ran a whole development programme as 51 written initiatives, each with its measurements and the decisions it declined. This site’s own readiness for agents was built the same way.
How an engagement runs
It starts with one task and its cases. We sit with the people who do it, write down thirty to fifty real examples with the right answers, and agree what the agent may do alone. Then we build the smallest agent that passes them, behind a review screen, in your infrastructure or your cloud account, with its access locked to what it needs. Then the next task. You own the code, the cases and the data, so the agent stays yours when the model under it changes. It is bought like the rest of our work, on the terms in what it costs.
If there is work in your trade that an agent should take off somebody’s desk, tell us what it is.
Take one task off somebody's desk — and measure it before you trust it.
It starts with thirty to fifty real cases from your trade, written with the people who do the work.
