MiroFish

Product Introduction

1. Overview: MiroFish is an AI-powered simulation and prediction engine designed for strategic planning and scenario analysis. It operates within the category of agent-based modeling and narrative intelligence platforms, transforming unstructured text inputs into dynamic, interactive simulations.
2. Value: Its primary benefit is enabling users to pressure-test strategies, policies, and narratives in a simulated environment before real-world implementation, uncovering hidden risks, audience reactions, and second-order effects that traditional forecasting methods often miss.

Main Features

1. Text-First, Multi-Agent Simulation: Users start with a plain-language question or seed document. The system autonomously orchestrates a backend workflow involving knowledge graph extraction, multi-agent simulation with defined personas, and structured reporting, all within a single chat interface.
2. Structured Prediction Reports: Each simulation generates a detailed result card containing a summary, key turning points, risk assessments, and clear paths for follow-up analysis, moving beyond simple text answers to actionable intelligence.
3. Knowledge Graph Foundation: The engine parses input material to construct a semantic network of actors, relationships, incentives, and factual anchors. This structured knowledge base ensures agents reason from a coherent world model, enhancing simulation fidelity.

Problems Solved

1. Challenge: Strategic planners, marketers, and policy analysts struggle to predict complex human and market reactions, which involve social dynamics, narrative spread, and incentive structures not captured in spreadsheets or linear models.
2. Audience: This tool is essential for product managers, brand strategists, policy advisors, market analysts, and communications teams who need to anticipate public sentiment and narrative evolution.
3. Scenario: A company planning a price increase can use MiroFish to simulate customer sentiment across different segments, model potential backlash paths, and identify which groups are most likely to resist, enabling proactive communication planning.

Unique Advantages

1. Vs Competitors: Unlike standalone chatbots or static analytics dashboards, MiroFish integrates the entire prediction lifecycle—from question to graph to simulation to report—into one continuous, conversational workflow, eliminating context switching and data silos.
2. Innovation: Its technical edge lies in the tight coupling of a knowledge graph engine with a multi-agent simulation framework, allowing for reasoning over structured relationships and emergent social dynamics directly from textual inputs like PDFs and policy drafts.

Frequently Asked Questions (FAQ)

1. What kind of files can MiroFish process? MiroFish can ingest and analyze text-based files including PDFs, Markdown (.md), and plain text (.txt) documents, extracting entities and relationships to build its simulation knowledge base.
2. How is MiroFish different from using ChatGPT for scenario planning? While ChatGPT generates text-based responses, MiroFish runs a structured, multi-step simulation involving graph building, agent interactions, and report synthesis, providing a systematic analysis of dynamics, risks, and turning points rather than a single answer.
3. What are typical use cases for the MiroFish Prediction Engine? Key use cases include campaign narrative stress-testing, pricing strategy reaction modeling, policy rollout impact simulation, and market narrative analysis to understand interactions between sentiment, incentives, and public discourse.