You already know the news. That's not the problem.
Every investor in a market has access to the same headlines, the same earnings calls, the same analyst notes. The edge was never in having the information. It was always in understanding what the field was doing with it — which way the collective decision energy was moving, and how close it was to a threshold.
Sentiment dashboards measure mood. They don't measure physics.
Fear and greed indices tell you where the crowd is. They don't tell you whether that fear is building toward a threshold crossing or dissipating through normal damping. Decision Physics does. Pressure accumulates with a measurable coefficient. Coherence across domains determines whether that pressure has anywhere to go.
Single-domain analysis creates the illusion of understanding.
A market moving on equity momentum while narrative is fracturing and policy is tightening is not the same as a market where all three are aligned. The difference determines whether the move sustains. You cannot read it from one domain. You need the field topology — all eight domains simultaneously, cross-referenced for resonance and coherence.
The field. Every domain.
All at once.
Every analysis fires 80 targeted searches across eight domains in parallel. No aggregation. No summarisation. Live data pulled, classified by the 50-dimension taxonomy, and cross-referenced for resonance.
From market to field topology in minutes.
Four phases. All automatic. Every model, chart and scoring table built from what the analysis actually found — no templates, no preset outputs.
Six live models.
Unique every run.
Not a template with the market name swapped in. Structural models built from what the analysis actually found this time, in this field, on this day.
Every signal is classified.
Not described.
Meta Intelligence never produces prose interpretations of signals. Every signal receives a type classification from the 10-category taxonomy, a horizon, a confidence rating and the specific dimension numbers that fired. This makes signals comparable across domains, markets and time.
50 dimensions.
Five families.
Every signal classified twice.
Each signal is assigned the specific taxonomy dimensions that fired in its detection. The scoring table ranks all signals by how many dimensions fired multiplied by confidence. This tells you which signals are structurally significant versus which are surface noise.