Structural Analysis Engine

Systems under
pressure create
patterns.

Describe a situation. The engine maps it against known structural patterns from 3,000 years of recorded system failures.

Situation Analysis

Describe a situation — any system under pressure. The engine identifies which structural patterns are active, what the trajectory looks like, and what signals to watch.

What-if events

Select events to test against the situation. Each one changes the conditions — the engine shows you what changes.

How It Works

The engine uses three structural analysis methods. Each one operates independently — together they cover different types of certainty.

01
Pattern Matching
The engine compares a situation against a library of structural patterns identified from historical system failures across 3,000 years. When a pattern matches, the historical outcome provides a reference trajectory. Different domain, same structure.
02
Decision Vectors
A decision vector is a structural force that shapes outcomes — role, institutional pressure, authority gradient. Once the setup is known, the prediction follows without personal data. The field determines the range of likely decisions.
03
Fragility Mapping
Inject controlled perturbations into a knowledge zone to find where stability ends. The method maps the exact threshold where a system shifts from stable to unstable — and whether it recovers or collapses.
04
Multi-Model Comparison
Run the same query through multiple AI models from different training origins. Where models agree, the answer is mainstream. Where they diverge, the territory is contested. Divergence itself is data — it maps the frontier of the known.
05
Evaluation Logic
Every input carries an interpretation distance (0 = raw event, 5 = AI consensus) and a certainty type (structural, measured, inferred, consensus, AI output). The system weights each claim by its type and domain match — not by authority or agreement.
06
Common Sense Validation
Common sense is the natural evaluation system every human has — pre-social, structural, universal. The engine uses a validated common sense library as a high-confidence evaluation layer. Crowd validation measures recognizability, not agreement.
Pattern Library

Eight structural signatures identified across 3,000 years of recorded system failures. Each pattern describes a sequence — the domain changes, the structure repeats.

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Common Sense Library

The engine uses a common sense library as an evaluation layer. You can help validate entries — if a statement is structurally obvious to you, that's a data point. No expertise required.

Passphrase
Anonymous. Your passphrase identifies your validations. Nothing is stored on your device. Unknown passphrases are sandboxed until reviewed.

“The single biggest obstacle to any form of progress is not wanting. Nothing else.”

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