Agent factories
We build a fleet of agents for one business process at a time, run it inside your infrastructure, and hand everything over once the work is stable.
Why pilots stall
The numbers below come from analysts and researchers, not from us. They describe the gap we work in.
40%+
of agentic AI projects will be cancelled by the end of 2027, Gartner predicted, citing costs, unclear value and weak risk controls.
23%
of respondents said their organisations were already scaling an agentic AI system somewhere in the business. 62% were at least experimenting with agents.
95%
of organisations studied were getting zero return from generative AI, according to MIT NANDA's preliminary 2025 report (52 interviews, 153 survey responses, 300+ public deployments).
How an engagement runs
Map
We sit with the people who do the work today, choose one process and write down what done looks like and how we will measure it.
Build
Agents, reviewers, tools and evals for that process, built in your environment and behind your access controls.
Prove
The factory runs next to your team on your live workload. You see the acceptance rate, the cost per accepted task and every failure.
Hand over
We run it together, then hand over the code, the runbooks and the evals. We offer ongoing support on agreed terms after hand-over.
What you keep
./source-code
Source code
Everything we build for your process, in your repository from the first commit. Our own reusable tooling stays ours and comes with a perpetual licence for you.
./evals-and-review-rules
Evals and review rules
The tests that decide whether an agent's work is acceptable, written with your experts.
./traces
Traces
A full record of every task: inputs, tool calls, review verdicts and cost.
./runbooks
Runbooks
What to do when a model changes, a tool fails or quality drifts.
./quality-and-cost-reporting
Quality and cost reporting
Acceptance rate, cost per accepted task and human minutes, per process and per week.
Security and compliance
- Least privilege
- Each agent gets scoped credentials for the tools it needs and nothing else. Access is logged.
- Prompt injection
- Content from documents, emails and tools is treated as data. We test each factory against known injection patterns before release.
- People approve what matters
- Actions that move money, change customer records or leave the company wait for a person.
- AI Act
- We document each system so you can meet your obligations as a deployer. After the 2026 amendments, most high-risk obligations under Annex III apply from 2 December 2027. Gibson Dunn, 2026 Our note on the delay
Questions we get
Which models do you use?
Whatever fits the task and your constraints: commercial APIs, models hosted in your cloud region, or open-weight models on your own hardware. The factory does not depend on a single vendor.
Do you need access to production data?
Only to what the process needs, through the same access controls your staff use. A lot of the early work can start on a copy.
How do you price the work?
Per process. After mapping it with you we send a fixed proposal for building and proving the factory.
Who runs the factory after launch?
Your team, with ongoing support from us on agreed terms. Everything is documented, so you are not locked in to us.
Where are you based?
In Lublin, Poland. We can work with companies anywhere in Europe, on site when it helps.
Have a process in mind?
Tell us what it is and how much work flows through it. We will tell you whether agents are a good fit, and say so if they are not.
Talk to us