SimSwarm

SimSwarm is an open-source multi-agent simulation engine built for scenario analysis. You upload any seed document — a press release, policy draft, earnings report, or news story — and SimSwarm spawns a configurable swarm of LLM agents that interact with each other around that scenario. The emergent behavior of those agents surfaces four outputs: a structured analysis report, an entity relationship graph showing how actors and concepts connect, prediction markets reflecting agent consensus on likely outcomes, and a full transcript of the agent conversations that produced the result.

The appeal is running "what if" simulations without manual modeling. Instead of writing agent personas and scripting interactions yourself, you drop in a document and let the swarm derive the dynamics. It's useful for analysts stress-testing how a product launch or regulation might land, researchers studying emergent LLM behavior, and strategists who want a fast second opinion on how a scenario could play out across different stakeholders.

Being open-source means you can inspect the agent architecture, adjust swarm size and personas, and self-host if the scenarios are sensitive.

Used by analysts, researchers, and strategists to run 'what if' scenario simulations by feeding a document to a swarm of LLM agents and reading their emergent output.