CYBRET AI is an autonomous security research and development laboratory that builds intelligent systems for understanding, reasoning about, and responding to cybersecurity threats at machine speed across complex digital environments. The platform operates through a four-layer architecture: Sensor Layer: Collects enterprise logs, network traffic, cloud telemetry, and identity data from across the environment. Reasoning Layer: Utilizes AI models, multi-agent systems, and security knowledge graphs to analyze and contextualize security data. Action Layer: Executes automated response, containment, remediation, and system hardening activities. Learning Layer: Continuously improves detection and response capabilities through machine learning. The core scientific focus centers on knowledge graph cybersecurity, which unifies identities, assets, logs, and threat signals into a single reasoning layer. This approach enables contextual detection, attack-path reconstruction, and machine-driven response intelligence by modeling relationships and behavior across the entire environment rather than analyzing security data in isolation. The research program studies AI-powered cyber attacks and autonomous adversaries to design defensive systems capable of countering next-generation threats. The lab develops automated pipelines for structuring, cleaning, and labeling security data at scale, transforming enterprise telemetry into training data for intelligent security systems. The productization pipeline translates research into operational security systems through a closed-loop process from research to prototypes to autonomous security systems deployed in enterprise and critical infrastructure environments.