For clients
AI agent systems
Large-scale agent platforms, architected for production, not demos.
Problem
An agent that works in a demo is a long way from one that can be left running for real users. In production it has to reach the right tools, answer from the right documents, handle images and speech as well as text, and stay inside limits on what it will do and say.
The job was to build that platform properly, not to show that an agent could be made to work once.
What we built
The platform and the parts that keep agents reliable in production:
- MCP tooling. Tools exposed to agents over the Model Context Protocol.
- Guardrails. Checks on what agents take in and what they send out.
- RAG and multimodal RAG. Retrieval over documents, and over images alongside text.
- Camera vision. Agents that work from live camera input.
- Voice agents. Spoken conversations in place of forms and menus.