An MCP-native agentic platform orchestrating planner/executor/critic agents over hybrid RAG with three-tier memory, budget enforcement, safety guardrails, and full observability. It exposes all capabilities as MCP tools, enabling natural-language control of document ingestion, retrieval-augmented generation, and multi-step AI workflows.
Enables running durable, traceable AI agents via LangGraph through a universal MCP interface, integrating with Hatchet for orchestration, logging, and retries. Provides tools for knowledge management (ingestion, RAG) and Kubernetes operations (diagnosis, auto-fix).
Provides AI agents with operational customer context, including typed revenue objects, persistent state, scoped tools, and human-in-the-loop handoffs through MCP, REST, and CLI.
Enables autonomous orchestration of vector search, knowledge graph queries, and web crawling through a single MCP interface, providing agentic RAG capabilities for AI assistants.
Provides comprehensive architectural expertise through specialized agents, resources, and tools for generating, evaluating, and modifying architectural designs.
