AI agents and automated workflows that run in production
An agent that answers well in a demo and an agent you can put in front of customers are separated by logging, permissions, cost limits and a way to stop it. We build the second kind: the process is mapped first, the model is chosen last, and every action it takes is written down.
What the work actually involves
Process before model
We map the work a human does today, then automate the part that is actually repetitive.
Agents with boundaries
Scoped permissions, spending caps, human approval on anything irreversible, and a full audit trail.
Documents and inbox work
Extracting, classifying and routing what arrives as PDFs, emails and scans — where most of the hours go.
Measured, not assumed
Accuracy tracked against a real sample, so you know what the automation gets wrong before your customers do.
How we work
We start by reading, not by quoting
Before a number exists we go through the brief, the existing code and whatever is already in production. You get a written plan with dates and the risks named — usually within a week. If the honest answer is that you do not need us, you get that instead.
A small senior team with one owner
Two to five engineers, one lead who is accountable for the outcome and answers your messages. No account manager relaying questions, no rotating bench, no juniors learning on your budget.
Everything is yours from day one
Repositories, cloud accounts, domains and pipelines are in your name from the first commit, not handed over at the end. When the engagement stops, nothing stops working.
Questions clients ask first
Will it hallucinate?+
Sometimes, which is why it is not allowed to act alone on anything that costs money or cannot be undone. The design question is not "will the model be wrong" but "what happens when it is" — and that answer is built before the agent ships.
Which model do you use?+
Whichever fits the task and the budget, and it is swappable by configuration. Anything wired so tightly to one provider that changing it means a rewrite is a commercial risk, not an architecture.
Does our data go into training?+
Not through us. We use API tiers that exclude your data from training, and where the data cannot leave your perimeter at all we say so and price the self-hosted option instead of pretending the question does not exist.
Are you the engineer, not the client?
We staff this work partly from independent developers and studios verified on our own platform, and the same platform is how contractors outside the US invoice American clients and get paid.
How that worksOther things we do
Custom software development for companies in the US, Canada and the EU
Websites and SaaS products, built to be measured
Systems architecture and cloud infrastructure
Putting AI inside a product that already has users
Demand generation for companies that sell something complicated
Tell us what you are building
A short description of the problem is enough to start. We reply with what we would do, what it would take, and what we would not touch.
Discuss a project