Trusted by traders and analysts

Are you an investment trader?
Use AI to understand drivers and estimate outcome odds before you invest.

From question to causal reasoning

Prediction markets give you prices. CausalTree helps you understand why probabilities might change.

Live causal traversal
Question
Start with uncertainty
🎯
Drivers
Key factors identified
🌳
Causal Tree
Relationships mapped
📊
Outcomes
Probabilities ranked
💡
Insights
Test assumptions
"You don't get answers. You get a structured way to think."

Causal trees, not black-box predictions

CausalTree doesn't "forecast the future." It builds a causal tree that shows what assumptions matter, how they influence outcomes, and which paths dominate probability.

Explainable

See why probabilities change. Every outcome is traceable to specific drivers and assumptions.

Adjustable

Try alternative assumptions. Adjust probabilities and watch outcomes reorder in real-time.

Transparent

Assumptions are always visible. No hidden layers, no mysterious algorithms.

💭 Always ask: "What assumption is driving this?"

Trusted by people who trade uncertainty

Futurety is used by traders, analysts, and decision-makers to reason about uncertain futures.

They use CausalTree to:

  • Break down complex questions into drivers
  • Stress-test narratives before committing capital
  • Understand what information would actually move probabilities
Polymarket
Traders
+
Kalshi
Users

use CausalTree for causal analysis

CausalTree is a thinking companion, not a signal service.

How people use CausalTree to reason about outcomes

1

Start with a question

"Will the Fed cut rates by June?"

2

CausalTree builds a causal tree

Inflation → Jobs → Guidance → Outcome

3

Try assumptions and evidence

"What if inflation surprises lower?"

4

Outcomes re-rank instantly

You see what actually moves the odds

Designed for uncertainty

CausalTree helps you:

  • Reason under uncertainty
  • Compare plausible futures
  • Understand belief changes

All models are assumption-based.

All probabilities are conditional.

That's the point.

Get started with CausalTree

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