AURA Control Layer Data Pipeline orchestrates multi-agent reasoning over telemetry, API streams, and user inputs through state normalization and threat detection. Data flows through a three-tier lake (Raw JSON/Avro, Curated Parquet, Aggregated Delta) while a dual-agent system (Planner and Critic/Evaluator) validates decisions against symbolic rules and compliance matrices. The pipeline enforces verifiable policies via a Digital Twin Validator and State Clone before action injection, with confidence scoring and human gateway approval preceding real-world actuation to grid switches or EV routes. This architecture demonstrates how to build trustworthy autonomous systems by combining ML serving endpoints with explainability, audit logging, and human-in-the-loop oversight. Fork and customize this diagram on Diagrams.so to adapt the control layer for your domain-specific agents and compliance requirements.