QSP-EF: Symbolic Intelligence Engine™

Predictive intelligence extension for anticipatory analysis across financial markets, critical infrastructure, strategic intelligence, and defense applications. Provides scalable detection of latent patterns and composite forecasting outputs within a dual-use framework.

Contamination-aware supervisory layer for model evaluation and forecasting. Supports safe probing, compliance auditing, and resilient operation under interference by quantifying and controlling measurement effects.

Modular collapse-based forecasting engine delivering adaptive, interpretable predictions across domains such as finance, defense, and crisis response, with emphasis on robustness and scalable deployment.

Symbolic overlay and multi-metric evaluation engine transforming model signals into composite, explainable intelligence indicators to support trustworthy and auditable AI decisions.

Cognitive security layer for AI deployments. Detects adversarial drift and poisoning attempts and supports resilience tracking, enabling secure and audit-ready forecasting pipelines.

Extends the architecture to defense and intelligence domains. Multi-sensor validation supports predictive warnings with measurable evaluation outputs and audit-ready traces.

Defensive cognitive security layer for user-facing AI and AR/UX exposure streams. Detects non-organic influence patterns across multimodal stimuli (text, audio, video, AR overlays, sensor-derived descriptors) and supports pre-exposure mitigation with audit-ready evidence records.

Observer-coupled protocol for validation of semantic coherence and trust calibration in forecasting systems, extending the QSP-EF architecture for explainable and auditable AI assurance across domains.