Simulates future scenarios from reports and data using agent-based modeling.
Product memo
Analysts, forecasters, and storytellers use agent-based modeling to simulate future scenarios from their reports and data. It builds parallel worlds from raw inputs, allowing deep interaction with agents to explore trajectories. This approach offers a dynamic, interactive way to test variables and inspect social evolution before real-world events unfold.
For who
Analysts, forecasters, and storytellers
Solves what
Simulating future scenarios from reports and data using agent-based modeling.
- Ontology and graph generation
- Parallel agent-based simulation
- Prediction report generation
In their own words
Upload Any Report. Simulate The Future Instantly.
A simple and universal swarm intelligence engine
From public opinion forecasting to literary continuation, it lets you inject variables, run social evolution, and inspect the likely trajectory before the real world catches up.
Commercial cues
Model
subscription
Free tier
No
Trial
Available
Pricing Strategy
MiroFish uses monthly subscription tiers tied to the listed plan limits.
- • Three tiers scale simulation capacity and support levels for varied user needs.
- • A free trial encourages adoption for recurring forecasting and scenario planning.
Operator context
Operating setup
Founded
May 2026
Platform
Web app
Audience
General
Market demand
MiroFish keyword demand
5 keywords
Market demand is Starter-tier market intelligence.
Derived from this product’s latest SimilarWeb keyword mix — directional demand, not proof.
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Small Team
About MiroFish Expand
MiroFish provides a unique approach to scenario simulation, enabling analysts, forecasters, and storytellers to transform raw reports and data into interactive, agent-based future scenarios. It builds parallel worlds where users can inject variables, run social evolution simulations, and inspect trajectories.
This capability helps users understand potential outcomes before real-world events occur. The platform offers features like ontology generation, graph construction, parallel simulation, and report generation, giving users deep interaction with agents to explore dynamic possibilities.
This specialized focus helps teams move beyond traditional forecasting by providing a more interactive and exploratory method for understanding complex systems.