AI agents for business,
built to run in production.
Agents are powerful and easy to get wrong. We build AI agents that do real work inside your systems, with the evals, guardrails, and cost ceilings that keep them honest, then hand them over. And we will tell you when an agent is overkill and a plain workflow is the better, cheaper, safer answer.
The honest question we ask first
Most 'agent' problems are better solved by a deterministic workflow with one or two model calls: cheaper, more predictable, easier to test. We reach for an agent only when the task genuinely needs to plan, use tools, and adapt over multiple steps.
Getting this call right is most of the value. An agent built where a workflow would do is a standing source of cost, latency, and surprise. We make the trade-off explicit before we build anything.
Agents that act inside your systems
We build agents that retrieve from your data, call your tools and APIs, and take real actions, with the integrations to your stack that make them useful rather than a demo. Tool use, memory, and orchestration are designed for your task, not bolted on from a template.
Every agent ships with an eval harness (a graded test set that tells us, on every change, whether it is getting better or worse), guardrails on what it can do, and a hard cost ceiling so a runaway loop cannot run up a bill.
Operated, then yours
Agents need operating: monitoring, drift detection, incident playbooks, and a human-in-the-loop where the stakes require it. We run yours with you during a support window, then hand it over with runbooks and the code in your repositories.
This is the Build & Run offer applied to agents specifically: code in your repos from day one, IP transfer in the contract, and a team that can keep running it after we step back.
Common questions.
Direct answers to the questions we get asked the most. If yours isn't covered, write to the team.
Start
Build an AI agent that earns its place in production.
Tell us the task. We will tell you honestly whether it needs an agent or a workflow, then build and run the right one.