An agent demo impressed everyone, but nobody will sign off on giving it production credentials or real customer data.
The agent works on the happy path and fails quietly everywhere else, and you have no way to measure which is which.
Behavior and cost are opaque: you cannot say what the agent did on a given task, why it did it, or what it spent doing it.
Map the work and the blast radius
We map the tasks the agent will own, the systems it touches, and what happens when it is wrong. That sets the tool permissions and the human escalation points before any orchestration is written.
Build the harness before the agent
The evaluation suite comes first: task success, tool-call accuracy, and regression cases drawn from real transcripts. Every change to the agent is scored against it, so improvement is a number and regressions are caught before users see them.
Wire tools through MCP with scoped permissions
Each tool gets the narrowest permission that still does the job, enforced at the MCP layer rather than in the prompt. Risky actions route to a human by design.
Run it observed, then hand it over
Tracing, dashboards, and per-task cost attribution ship with the system. Your team gets the runbooks and the harness, and keeps both when we leave.
Which models and frameworks do you use?
Whatever fits the task. We work with Claude, OpenAI, and open-weight models, and we keep the orchestration layer thin so you can change models later. The evaluation harness is what makes that change safe: swap the model, rerun the suite, compare the scores.
What happens when the agent gets something wrong?
We design that path up front. Risky actions route to a human before they execute, failures trace back to the step that caused them, and each incident becomes a regression case so the same failure is caught automatically next time.
Can you start from the agent we already built?
Yes, and most engagements do. We baseline your prototype against an evaluation suite first, keep what scores well, and rebuild what fails. You see the numbers for both before we change anything.