We design agent architectures that go beyond demos — orchestration, tool use, guardrails, and real evals.
The gap between an agent that works in a notebook and one that works in production is wide. It’s not the model — it’s everything around it: how tools are exposed, how state is managed, what happens when the model gets it wrong, how you measure whether it’s actually getting better.
What we typically deliver
- Agent architectures (single-agent, multi-agent, tool-augmented) chosen for the actual problem, not the trend
- Tool design and integration — APIs, code execution, retrieval, function calling
- State management, memory, and conversation handling
- Guardrails: input/output validation, safety filters, fallback behaviors, human-in-the-loop where it matters
- Evaluation pipelines (offline + online) so you know whether changes actually help
- Observability: tracing, logging, and the right dashboards for an LLM-powered system
Who this is for
Teams that have a working prototype and now need to make it reliable, observable, and safe enough to put in front of real users — or teams who want to skip the prototype-that-never-ships phase entirely.