Strategic Interaction Simulation Powered by AI Agents
SparkFish uses multi-agent AI to model how different actors behave in any scenario — business negotiations, market dynamics, geopolitical situations, competitive strategy. Upload a seed document, run a simulation, and get actionable predictions backed by agent-based modeling and LLM reasoning.
SparkFish runs a full agent-based simulation pipeline — from document analysis to entity extraction to multi-round strategic interaction.
Feed SparkFish a business plan, geopolitical brief, market analysis, or any strategic document describing the scenario you want to analyze.
→AI extracts key actors, their interests, constraints, and relationships. SparkFish builds a structured map of the strategic landscape.
→Each actor gets an AI agent persona. Agents interact across multiple rounds — negotiating, competing, cooperating — following their programmed strategies.
→SparkFish synthesizes the simulation results into a structured prediction report with probability-weighted outcomes and strategic recommendations.
SparkFish combines multi-agent simulation with LLM reasoning to give you insights that single-model analysis can't match.
Each actor in the simulation gets a dedicated AI agent with a distinct persona — interests, constraints, behavioral tendencies, and strategic objectives.
Upload any strategic document — PDF, text, URL — and SparkFish extracts the relevant actors, relationships, and scenario parameters automatically.
SparkFish synthesizes the simulation into a structured report with probability-weighted outcomes, key decision points, and strategic recommendations.
After a simulation, ask SparkFish follow-up questions in natural language. Probe specific outcomes, actor motivations, or alternative scenarios with a conversational layer on top of the structured results.
SparkFish supports Claude, GPT-4, Gemini, and local models via Ollama. Configure the model that fits your use case and budget.
SparkFish is fully open source under AGPL-3.0. Fork it on GitHub, run it locally, or deploy it on your own infrastructure. No vendor lock-in.
SparkFish is a strategic analysis tool. It's most powerful when the outcome depends on multiple actors with different goals, constraints, and information.
SparkFish walks through a structured simulation pipeline — each step feeds the next.
After uploading a seed document and configuring actors, SparkFish runs a multi-round simulation and delivers a structured report. Here's what the output contains:
SparkFish combines the CAMEL multi-agent framework with the OASIS simulation system, powered by LLMs for realistic actor behavior.
SparkFish is built on a proven multi-agent AI architecture: CAMEL handles role-playing agent coordination, OASIS handles the structured simulation loop, and LLM backends provide the reasoning for each actor.
Run SparkFish on your own infrastructure. Bring your own API keys. The simulation logic is transparent and auditable — no black-box cloud service.
SparkFish is open source and self-hosted. Fork it on GitHub, run it locally, and start modeling your strategic scenarios today.