A production-grade AI architecture for virtual agents: orchestration, knowledge (RAG), security, observability, and continuous evaluation.

Architecture

Terranoha.ai provides a production-grade architecture for building and operating virtual agents such as Emmie. Instead of treating AI as a standalone chatbot, we structure it as an end-to-end system that can reason, retrieve, act, and verify—with governance and traceability.

The architecture is built around three core layers:

  • Agents: goal-driven components that plan tasks, call tools, and produce structured outcomes. They are designed with controlled memory, clear policies, and safe tool usage.

  • Orchestration: the execution backbone that manages state, retries, idempotency, long-running workflows, and human approvals—so automation remains reliable under real constraints.

  • Knowledge layer (RAG): a governed retrieval layer that connects agents to your internal documents and systems with hybrid search, reranking, access controls, and citations.

To make this usable in production, the architecture includes security by design, observability end-to-end, and continuous evaluation to monitor quality, cost, and reliability over time.

Explore the building blocks:

  • /platform/agents

  • /platform/orchestration

  • /platform/knowledge