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AI agent development
Systems that complete work, with a human in the loop where it matters.
What this actually involves
An agent that can act is only useful if it can be trusted to act. We scope tool access narrowly, make every step observable, and design the approval points before writing the orchestration, so the system degrades into a queue rather than into a mistake.
- Tool and permission design with explicit blast-radius limits
- Step-level tracing so any run can be replayed and audited
- Human approval gates on irreversible actions
- Retry, fallback, and escalation paths for every failure mode
When it fits
- The work is a repeatable process with clear steps, such as intake, lookup, and update.
- You can define which actions the agent may take and which need a human to approve.
- Errors are recoverable, or a review step can catch them before they become costly.
When it does not
- The process changes every time. An agent cannot follow rules that do not exist.
- An action cannot be undone and nobody will review it first.
- A plain script or an existing automation tool already covers it.
What we need from you
- A written or recorded walkthrough of the process as people do it today.
- A list of the systems the agent will touch and the permissions it should have.
- A rule for which cases go to a human.
Ready to move from AI experiments to AI in production?
A thirty-minute call. We assess the use case, name the risks, and tell you honestly whether we are the right fit.