agent-governance

Prevent prompt injection by implementing semantic intent classification to detect and block harmful user prompts before execution. This approach intercepts malicious inputs early, ensuring agents only process authorized commands and interact safely with external tools.

Trust scoring in multi-agent workflows is a mechanism to track agent reliability and manage interactions based on trust metrics. It evaluates historical actions to dynamically adjust permissions, preventing unreliable agents from executing critical or sensitive operations.

Enforce policy-based access controls for AI deployments by defining strict rules for tool usage, content filtering, and rate limiting. This restricts agents from executing arbitrary shell commands or exposing sensitive data like API keys during production workflows.

Create an audit trail for AI agent actions by maintaining immutable logs of all tool calls and operations. This ensures strict accountability and provides a reliable debugging record for compliance requirements in production agent systems.

Yes, you can implement AI governance patterns for assistants accessing company databases by applying policy enforcement and intent classification. This secures data access while strictly forbidding the execution of arbitrary shell commands or exposing sensitive credentials.