Enables deterministic zero-trust security for AI agents, providing prompt injection protection, PII scrubbing, and policy enforcement before agentic actions reach production systems.
A data-loss-prevention (DLP) layer for AI agents that intercepts document reads, scans for sensitive data, and redacts or blocks it before it reaches the model, with audit logging.
Provides AI ingress governance by masking prompts, classifying risk, and enforcing tool policies before agent calls reach model providers or sandboxes.
Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.
Enables secure interaction between LLMs and MCP tools by applying zero-trust security controls, including sensitive data masking, file system protection, and policy enforcement.