A platform for deploying 6+ autonomous multi-agent systems using LangGraph stateful graphs, Google Studio AI, and Groq with cross-agent delegation.
This platform enables the rapid creation, testing, and deployment of autonomous multi-agent systems built on LangGraph's stateful graph execution model. Rather than simple sequential chains, agents in this system can branch, loop, delegate to sub-agents, and make conditional decisions based on tool results.
Over 6 multi-agent systems have been deployed on this platform, covering use cases from document processing automation to research synthesis and code review. Groq provides ultra-fast inference for latency-sensitive agent steps, while Google Studio AI handles complex multi-step reasoning tasks.
The platform includes a monitoring dashboard, agent execution tracing, and a REST API for programmatic agent invocation — making it suitable for integration into production enterprise workflows.
Understanding state schemas, nodes, edges, conditional routing, and graph compilation.
Building a supervisor agent that routes tasks to specialized worker agents based on task type.
Giving agents access to web search, Python REPL, database connectors, and file readers.
Configuring different LLM backends per agent node based on speed vs. reasoning requirements.
Using LangSmith for full agent execution traces, token counts, and latency profiling.
Building a FastAPI server and Streamlit monitoring dashboard for deployed agent systems.