Clarus Invariant PRO

Clarus Coherence Framework Clarus develops coupling-based coherence datasets that model how complex systems remain stable, fragment, and recover under stress. Most analytics optimize components in isolation. Clarus models interaction geometry — where instability actually begins. The framework operates across five layers: Coherence Detection Baseline stability and early drift detection System Coupling Pair, triadic, and quad-node interaction modeling Collapse Geometry Non-linear cascade and failure surface prediction Recovery Orchestration Intervention sequencing under pressure Governance & Steering Decision topology across interacting systems Multi-Node Coupling Model At the core is coupling geometry. Pair interactions reveal local strain Triads expose instability loops Quad coupling predicts systemic events Blackouts. Capacity overload. Trial failure. Market disruption. These events are coupling failures — not isolated errors. What Each Release Includes Structured datasets Coherence scorers Cascade prediction models Stress-test and simulation primitives All datasets are designed for reproducible evaluation and cross-domain comparison. Research and Enterprise Collaboration Clarus is building: Production-scale coherence monitoring infrastructure Large multi-domain coupling datasets Quad-coupling and network-level models Real-time drift detection systems Custom coherence scorers for deployment environments We welcome collaboration on: Large domain datasets Enterprise monitoring pipelines Custom scorer development Red-team and stress-test frameworks Cross-domain coupling research Contact For enterprise partnerships or dataset co-development: Contact: [team@loopwell.ai] Please include organization and domain of interest.