Launch brief
Positioning, audience, release plan, feature notes, objections, and the story your team wants the market to hear.
Market narrative simulation
Market Simulation AI
Test how customers, competitors, investors, and public narratives may react to a launch, pricing move, or market entry before the real market answers for you.
Built for market narrative simulation, not certainty. Every result should be reviewed against real evidence before an operating decision.
Scenario tape / illustrative
Market narrative simulation for a pricing move
R1
Power usersValue reframed as loss
R2
CompetitorsComparison narrative spreads
R3
Mainstream buyersTrust question becomes dominant
Dominant risk
Trust erosion
Pressure source
Price framing
Evidence gap
Segment elasticity
Input
Briefs, research, pricing, public sources
Engine
Actor graph + multi-round agent reactions
Output
Narrative risks, assumptions, next questions
What to bring
Start with the market evidence you already have.
A useful market simulation has to be honest about the input. MiroFish works best when the scenario is grounded in source material, not when it invents a market from a vague wish.
Competitor context
Incumbent positioning, comparison pages, analyst notes, user complaints, public posts, or review snippets.
Pricing proposal
New packages, migration rules, customer segments, support risks, and the reasoning behind the price change.
Where it earns its keep
Rehearse the market response, not just your own argument.
Most plans describe what the company will do. A useful simulation asks what everyone else does next.
Product launch01
Find the misunderstanding before it becomes the story.
Model how buyers, competitors, creators, and media interpret the same launch brief—and where your message loses control.
Output / Messaging risk
Market entry02
Test a new position against the market around it.
Explore how incumbents, customers, partners, and regulators may respond when a new offer changes their incentives.
Output / Stakeholder response
Pricing change03
See which objection spreads, and who amplifies it.
Stress-test a pricing narrative across customer segments before committing to a public announcement.
Output / Reaction path
A market is a system of reactions.
MiroFish treats your question as a world to construct and observe—not a prompt to answer once.
Stage 1
Ground the market
Upload research, launch plans, interview notes, or a public source. MiroFish extracts actors, claims, and constraints.
Stage 2
Build the synthetic world
Turn the evidence into a relationship graph where agents have distinct roles, incentives, and memory.
Stage 3
Run competing paths
Let reactions unfold over multiple rounds so second-order effects can emerge instead of being guessed in one prompt.
Stage 4
Interrogate the result
Review the likely trajectory, key risks, evidence lines, and the assumptions that would change the outcome.
What the report should answer
A sharper set of questions before the decision.
- The market narrative most likely to form first
- The actors that can amplify or redirect that narrative
- The second-order reaction your team is likely underestimating
- The evidence gap that would make the simulation less reliable
- Follow-up questions to pressure-test the result
What it does not give you
A magic number disguised as certainty.
- Guaranteed sales, revenue, or market-share forecasts
- A substitute for customer research or experimentation
- Live market data unless you provide a current source
- A decision made without accountable human judgment
Why not just ask a chatbot?
Market simulation needs a world, not one answer.
The difference is structure. MiroFish makes actors, incentives, and reaction rounds visible so the team can argue with the forecast instead of accepting it.
Reasoning structure
Chatbot
One compressed answer
MiroFish
Graph of actors, incentives, and constraints
Market behavior
Chatbot
Summarized as advice
MiroFish
Simulated as multi-round reaction paths
Reviewability
Chatbot
Hard to inspect after the answer
MiroFish
Report, risk trail, assumptions, and follow-up questions
FAQ
Market simulation AI, without the fog.
The useful boundary is simple: explore plausible behavior, expose assumptions, then verify against reality.
What is market simulation AI?+
Market simulation AI uses models to explore how different market participants may react to a proposed event, such as a product launch, pricing change, or market entry. MiroFish approaches this as a multi-agent scenario exercise grounded in the evidence you provide.
How is this different from asking an AI chatbot for a forecast?+
A single chatbot response compresses the market into one line of reasoning. MiroFish first builds a graph of actors and constraints, then simulates interactions over multiple rounds and produces a report you can inspect and question.
What is market narrative simulation?+
Market narrative simulation focuses on how a market story may form around a decision. Instead of only asking whether an idea is good, it examines who interprets it first, which objection spreads, and what evidence could change the path.
What evidence can I use in a market simulation?+
You can use PDF, Markdown, or plain-text files, as well as a public HTTPS source. Useful inputs include market research, customer interviews, competitor notes, launch briefs, pricing proposals, and policy documents.
Can market simulation AI predict sales or market share?+
MiroFish is designed for scenario analysis, not guaranteed numerical prediction. It can surface plausible reaction paths, narrative risks, stakeholder pressure, and evidence gaps, but it should not replace validated demand data or financial modeling.
Who should use an AI market simulation?+
Product marketers, founders, strategy teams, researchers, communications teams, and policy analysts can use it to challenge assumptions before a consequential decision or public release.
Related simulation paths
Split the market question into sharper decisions.
Market simulation is the umbrella. These focused pages go deeper on launch, pricing, and competitor pressure so the next click matches the user intent.
Launch reaction
Product Launch Simulation AI
Test buyer understanding, competitor framing, pricing objections, and GTM risk before launch.
Open Product Launch Simulation AIPricing pressure
Pricing Simulation AI
Rehearse churn narratives, package migration risk, and customer objections before a pricing change.
Open Pricing Simulation AICompetitor response
Competitive Intelligence AI
Simulate rival counter-positioning, buyer comparison frames, sales pressure, and proof gaps.
Open Competitive Intelligence AIThe market will react anyway
Choose whether you meet that reaction before or after launch.
Bring the brief, research, or decision you are already working on. MiroFish will turn it into a scenario you can inspect.
Start a market simulation