AI Technology
The Engine Behind the Insight
A multilayered analysis stack where neural networks, spatial mapping, and cognitive algorithms converge — built with privacy at its core.
Core Capabilities
Four Pillars of Analysis
Each pillar is independently validated and works in concert with the others to produce multilayered neural analysis.
Neural Network Pattern Recognition
Deep convolutional and graph networks trained on tens of thousands of validated neurograms and brainwave datasets detect structural signatures with 99.4% accuracy — from micro stroke deviations to global symmetry collapse.
Spatial Color-Geometry Mapping
Every artwork is projected into a joint color-geometry space: hue saturation, spatial placement, line curvature, and figure proportion are mapped together, revealing relationships invisible to single-axis analysis.
Cognitive Algorithms
Purpose-built cognitive algorithms translate mapped patterns into psychological indicators — attention, stress, creativity, emotional regulation — each scored with a calibrated confidence interval.
Data Privacy Standards
All submissions are encrypted in transit and at rest, processed in isolated analysis environments, and never used for model training without explicit consent. You control retention and deletion of every artifact.
Inside the Stack
Multilayered Neural Analysis
A single drawing or brainwave trace is never read once. Our stack passes every submission through successive analysis layers — each refining, challenging, and confirming the last — so the final report reflects convergent evidence, not a single model's opinion.
Layer 1
Signal Extraction
Stroke, color, pressure, and waveform data isolated at sub-pixel precision.
Layer 2
Pattern Classification
Neural networks classify structural signatures against validated libraries.
Layer 3
Cognitive Translation
Cognitive algorithms convert patterns into scored psychological indicators.
Layer 4
Convergence & Report
Cross-layer agreement is verified before the instant report is generated.
Trust & Compliance
Data Privacy Standards
Psychological data deserves the highest standard of care. Privacy is engineered into every stage of the pipeline.
End-to-End Encryption
Every submission is encrypted in transit (TLS 1.3) and at rest (AES-256). Decryption occurs only inside isolated analysis environments.
Consent-Based Training
Your neurograms, brainwave data, and artwork are never used to train models without explicit, revocable consent.
Full Data Sovereignty
Request deletion at any time. All derived artifacts — pattern maps, reports, and intermediates — are purged on request.