Secure Control
Secure Control refers to the architectural and operational mechanisms ensuring that ai-agents operate within defined safety boundaries, permission scopes, and visibility constraints in production environments. It encompasses runtime enforcement, auditability, and real-time monitoring of autonomous actions.
Core Principles
- Least Privilege Execution: Agents must only access resources explicitly granted for specific tasks.
- Real-time Visibility: Continuous monitoring of agent decision-making processes and external interactions.
- Deterministic Guardrails: Pre-defined constraints that prevent unauthorized or harmful actions regardless of model output variability.
Implementation & Tools
- Archest.AI: An open-source enterprise platform designed for secure production deployment.
- Provides integrated control and visibility layers for AI agents.
- Built by the team behind Grafana On-Call, leveraging existing observability expertise.
- Demonstrated integration with ollama for local model execution with enforced security policies.
- See detailed analysis: Archest.AI: Secure Control and Visibility for Production AI Agents
Related Concepts
- AI Agent Safety
- Runtime Enforcement
- Observability