Deepmiro

DeepMiro runs multi-agent simulations to predict how communities respond to events or policy changes. It extracts entities from documents, spins up hundreds of AI agents with distinct personalities and social networks, then simulates interaction across Twitter-like and Reddit-like platforms. The MCP exposes tools to trigger predictions, query simulation status, retrieve structured reports, and chat with individual agents post-simulation. Behind the scenes it uses GraphRAG for entity extraction, TWHIN-BERT for social embeddings, and SurrealDB for agent memory and relationships. Useful when you need emergent behavior forecasting that goes beyond single-prompt analysis, like testing policy drafts, market scenarios, or narrative outcomes before they play out in the real world.