SceneSignal

SceneSignal is an autonomous visual incident intelligence system that transforms chaotic industrial accident photographs into evidence-grounded, court-admissible forensic dossiers. When catastrophic failures occur at petrochemical refineries, construction sites, or power plants, human investigators face dozens of disorganized photos, subtle micro-fractures, and uncertain causality. Traditional AI hallucinates unfounded theories without spatial grounding. SceneSignal couples two of Meta's newest frontier models into a unified forensic pipeline: 1. Spatial Perception (Meta SAM 3.1): Utilizes Promptable Concept Segmentation via the Meta Model API (/v1/responses) across 15 specialized hazard categories (shear deformity, containment breaches, pooling chemicals, thermal scarring) to detect micro-anomalies and anchor precise pixel coordinates. 2. Forensic Multimodal Reasoning (Meta Muse Spark 1.3): Ingests multi-camera drone and ground captures within its 1M-token context window to cross-reference spatial geometry, reconstruct chronological causal sequences (T+1, T+2, T+3), and calculate actuarial risk exposure. 3. Epistemological Grounding: Completely eliminates hallucinations by strictly isolating findings into OBSERVED (pixel-grounded), INFERRED (causal timeline), or HYPOTHESIS (unobserved theory requiring physical testing). Every finding is bidirectionally linked to its exact image coordinates. 4. Courtroom & OSHA Compliance: Computes SHA-256 cryptographic hashes for full chain-of-custody verification and exports one-click court-admissible PDF dossiers.