Agents that do the work, not just answer questions

A chatbot produces text. An agent takes actions: it calls your APIs, reads and writes records, and works through a multi-step task until it is done or it hits a boundary you set. The engineering difference is mostly in what surrounds the model: tool access, permissions, retries, evaluation and logging.

A scoped first workflow typically reaches production in eight to twelve weeks: roughly two weeks of discovery, four to six weeks of build and evaluation, then a staged rollout. Broader multi-agent programmes run longer, but we deliberately ship one working workflow before expanding.

No. We work inside your cloud account and your data boundaries by default. Where regulation or policy requires it, we deploy open-weight models on infrastructure you control so nothing leaves your environment.

It will sometimes, so the system is designed for that. Irreversible actions route to a human, every run is logged and replayable, and the evaluation suite catches regressions before deployment. The goal is a known, measured error rate that beats the process it replaced, not an imagined perfect one.

Yes, and it is usually the better outcome. We can build alongside your team and hand over with documentation and training, or run the system ourselves. Being dependent on us is not a goal we design for.