AI agents that don't just answer: they get the work done

A chatbot answers questions through conversation. An agent takes action: it plans multi-step tasks, calls tools and systems to actually do things, and handles the results. Agents are far more capable and, correspondingly, require more engineering around safety, observability, and control.

When engineered properly, yes. We calibrate autonomy to the stakes, going fully autonomous for low-risk tasks and requiring human-in-the-loop approvals for high-consequence ones, and we instrument every action for observability and audit. Safety comes from the system design, not from trusting the model blindly.

Yes. We connect agents to your APIs, data, and tools through structured, permissioned integrations, so they take real action across the systems you already use.

We design for it: guardrails constrain what agents can do, human checkpoints gate risky actions, and full tracing lets you catch, debug, and correct issues. Agents degrade gracefully rather than acting unpredictably.

It depends entirely on the stakes of the task. We design the right level for each workflow: more autonomy where errors are cheap and reversible, more human oversight where they aren't. There's no one-size answer, and we'll recommend based on your use case.

Yes, and we recommend it for high-stakes actions. We build approval steps and review checkpoints so humans stay in control where it matters, while routine steps run automatically.

A focused agent for a defined workflow typically takes six to ten weeks. We start with a constrained scope, prove it works safely, then expand its capabilities and autonomy.