MiroFish is an AI simulation chat tool for scenario prediction. It turns text, PDF, MD, and TXT input into graph building, simulation, reporting, and follow-up chat through one continuous prediction workflow. Instead of returning a single isolated answer, MiroFish keeps structure, personas, social dynamics, and report synthesis in one sequence, so users can rehearse plausible reactions before making a decision.
The workflow begins with seed material: a plain-language question, report, policy draft, market note, or story fragment. From there, the system extracts actors, relationships, pressures, and factual anchors into a knowledge graph so agents reason from structure. Agent simulation then lets personas interact across short-form and threaded social surfaces over multiple rounds. The prediction report condenses emergent behavior into turning points, risks, confidence signals, and follow-up paths. Finally, deep interaction lets users continue asking questions against the generated world rather than stopping at a static answer.
MiroFish is text-first. Users start with a question and then decide whether supporting files are necessary, without losing the speed of chat. PDF, Markdown, and text files work best when they contain concrete actors, incentives, constraints, or prior context, such as a strategy memo, product FAQ, policy brief, market note, or customer research summary. Multi-agent processing runs graph building, simulation, and reporting behind the scenes while keeping the user inside a single conversation. Result cards drop a structured result below each answer with a summary, a report entry point, and a follow-up path.
Use cases center on scenarios where reaction matters more than a static answer. Campaign Test pressure-tests a launch narrative before it goes public, simulating how audience groups might amplify, resist, or reinterpret a message. Pricing Reaction explores the friction behind a price increase by modeling customer sentiment, value perception, and likely objection paths across segments. Policy Stress Test finds groups, incentives, and loopholes in a policy rollout as a tabletop exercise for controversy, coalition formation, and second-order reactions. Market Narrative watches narrative, incentives, and sentiment interact where spreadsheets miss the feedback loop between analysts, retail attention, and public discourse.
Report previews show the kind of structure a visitor can expect: an executive summary, risk signals, narrative paths, and follow-up questions. A sample scenario asks which customer groups resist a price increase first and what narrative makes the change recoverable. Risk signals include early backlash from price-sensitive segments, narrative compression into a simpler accusation, and influencer framing that outruns the official message. Narrative paths note that a value story holds if benefits are concrete, a skeptical thread grows if comparison charts are absent, and supporters need reusable language rather than only a launch post.
MiroFish positions itself as exploratory decision support rather than a guaranteed forecast. It is meant as a way to rehearse plausible reactions before using judgment, analytics, and real-world validation. The site also offers practical playbooks: write a sharper prediction prompt by naming the decision, audience, likely trigger, and time horizon; use files as reality seeds; and read the report like a rehearsal, looking for resistance signals, narrative bridges, and assumptions worth checking with real data.
