Forecast question
The market move, launch, policy, crisis, competitor action, narrative shift, or strategic decision you want to explore.
Evidence-grounded forecasting
AI Forecasting Tool
Use MiroFish as an AI forecasting tool for market moves, policy shifts, launches, incidents, and strategic decisions where actors, incentives, and timing shape the outcome.
Built for scenario planning, not certainty. Every output should be reviewed against real evidence before an operating decision.
Scenario tape / illustrative
Forecast path for a strategic market decision
R1
Source evidenceBaseline signal appears
R2
Affected actorsReaction path splits
R3
Decision contextForecast question sharpens
Dominant signal
Actor incentive
Forecast risk
Missing evidence
Review target
Decision trigger
Input
Brief, data, research, public sources
Engine
Actor graph + multi-round forecast paths
Output
Forecast report and evidence gaps
What to bring
Bring the evidence behind the forecast question.
An AI forecasting tool is most useful when it starts from concrete source material: market context, stakeholder signals, prior behavior, constraints, and the decision you need to review.
Evidence packet
Research notes, reports, customer conversations, articles, sales evidence, historical context, or public material that grounds the forecast.
Actors and constraints
Customers, competitors, institutions, communities, teams, incentives, timelines, dependencies, and non-negotiable limits.
Where it earns its keep
Forecast the path, then inspect the assumptions.
Forecasting is not a single number when the future depends on people. MiroFish helps teams see which actors, signals, and weak assumptions shape the forecast.
Market forecasting01
Test how a market story may move.
Explore how buyers, competitors, analysts, and channels may react as new evidence enters the market.
Decision forecasting02
Find the trigger that changes the recommendation.
Identify which assumption, actor, or external signal would make the team revise the plan.
Risk forecasting03
Surface second-order effects early.
Use multi-round simulation to inspect how the first reaction may create the next risk.
Useful AI forecasting needs evidence, actors, and review.
MiroFish turns your source material into an actor graph, runs reaction rounds, and produces a forecast report that can be questioned instead of accepted blindly.
Stage 1
Ground the scenario
Upload source material and define the decision, event, or message you want to test.
Stage 2
Build the actor graph
Map the people, groups, incentives, constraints, and memory that shape the reaction.
Stage 3
Run reaction rounds
Let the simulated actors respond over multiple rounds so the second-order path appears.
Stage 4
Question the report
Review the trajectory, risks, weak assumptions, and what evidence would change the conclusion.
What the report should answer
The report should show what drives the forecast.
- Which actor or signal matters most
- Which forecast path is most fragile
- Which assumption needs better evidence
- Which second-order reaction may change the outcome
- Which next question should guide the decision
Boundary conditions
Not a prediction oracle.
- Not guaranteed future prediction
- Not a substitute for validated data, expert judgment, or financial modeling
- Not live monitoring unless current sources are provided
- Not useful when the forecast question or evidence is too vague
Why MiroFish
An AI forecasting tool should make uncertainty inspectable.
Generic AI can give a confident forecast-style answer. MiroFish focuses on the path, evidence gaps, and assumptions behind the forecast.
Forecast basis
Generic AI
Summarized intuition
MiroFish
Evidence, actors, constraints, and memory
Future path
Generic AI
Single answer
MiroFish
Multi-round forecast paths and second-order effects
Decision review
Generic AI
Hard to audit
MiroFish
Inspectable report, assumptions, and follow-up questions
FAQ
AI forecasting tool, built for scenario review.
Use it to inspect plausible futures, not to pretend uncertainty has disappeared.
What is an AI forecasting tool?+
An AI forecasting tool helps teams explore plausible future paths from evidence, actors, constraints, and assumptions. MiroFish does this with actor graphs, multi-round simulation, and inspectable reports.
Can MiroFish predict the future exactly?+
No. MiroFish is designed for forecasting and scenario planning support, not certainty. It helps reveal plausible paths, weak assumptions, and evidence gaps.
What can I forecast with it?+
You can forecast market reactions, launch narratives, policy response, public opinion pressure, competitor moves, customer adoption risk, and other actor-driven scenarios.
What inputs should I provide?+
Provide a clear forecast question plus source material such as reports, research notes, market memos, customer evidence, public articles, timelines, or stakeholder context.
How is it different from a normal AI answer?+
A normal AI answer often gives one summary. MiroFish builds a scenario system first, runs reaction rounds, then gives a report you can inspect and question.
Related simulation paths
Follow the risk into the next decision.
Most decisions do not stay inside one category. These adjacent use cases help teams test the next market, customer, or public reaction path.
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Stock Market Simulator
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Turn uncertainty into a forecast you can inspect.
Bring the question, source material, and actors. MiroFish will turn them into an AI forecasting run with visible assumptions.
Start an AI forecast