We build AI agents that go beyond the chatbot: systems that reason about your context, decide the next step, call tools and carry out real work, with the reliability production demands.
An agent that dazzles in the demo and breaks in production is not an agent. It is an expensive prototype.
Most "agents" stop right there: they perform well in a controlled demo and fall apart on the first real edge case. The problem is rarely the model. It is the engineering around it: orchestration, reliable tools, limits on what the agent can do, observability and error recovery. That layer is exactly what decides whether an agent becomes a production system or stays stuck in the lab.
Agents that call APIs, query databases, take actions and check their own output, with guardrails that block what must never happen.
Several specialized agents coordinated by an orchestrator, each one owning a piece of the problem. Sturdier than a single monolithic agent.
Assistants that understand intent, hold context and resolve things end to end, wired into your systems rather than into a generic chat window.
Evaluation suites that measure accuracy before deploy, and telemetry that shows, in production, where the agent gets it right and where it slips.
A chatbot answers questions. An AI agent decides and acts: it chooses which tools to use, carries out multi-step tasks, queries systems and checks its own result before responding. It is the difference between informing and solving.
An agent focused on one well-defined workflow usually reaches production in 6 to 12 weeks. We start with immersion and a diagnostic to size scope, risk and ROI before we build.
No. We design the orchestration decoupled from the model, so you can switch providers (Claude, GPT, open models) without rewriting the system.
Tell us the context. Within 48 hours we come back with a point of view. If it is worth doing, we move forward. If not, you leave with clarity.
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