AgentControl is a security and authorization platform designed to govern autonomous AI agents operating within enterprise environments. It provides context-aware enforcement of policies across agent-to-agent, model-to-API, and model-to-data interactions, controlling what AI agents can access, request, and execute based on real-time contextual data. Key capabilities include: - Context-aware authorization driven by data relationships, purpose, and consent evaluated in real time - Secure model coordination (MCP) to manage how AI agents communicate, retrieve data, and trigger actions across systems - Dynamic policy orchestration that adjusts agent permissions instantly as risk, context, or conditions change - Audit and explainability features that trace every agent action back to data provenance and policy decisions AgentControl addresses risks such as agents accessing unverified data sources, unaccountable API calls, context loss between data and decision logic, and compliance gaps created by AI operational speed. The platform is aimed at organizations deploying agentic AI at enterprise scale, providing fine-grained authorization controls at every layer of the AI stack while maintaining auditability and policy alignment without requiring human intervention for each decision.