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Provides an infrastructure to govern AI agents with runtime policy enforcement. It allows companies to ensure AI agents operate within defined boundaries and provides audit evidence for compliance. Enforcement occurs…

Secures autonomous agents by defining boundaries, signing reasoning, and screening model calls.

Secures LLM agents against prompt injection by scanning for vulnerabilities and blocking unsafe tool calls.

Blocks prompt attacks, scores agent trajectories, and traces execution steps for artificial intelligence agents.

Screens commands and tool calls for AI agents on supported Linux hosts to enforce runtime security.

Enables control over autonomous AI model calls, tool invocations, and agent actions. Real-time policy enforcement with cryptographic evidence is provided.

Provides runtime security for AI agents by blocking prompt injection, malware, credential theft, and runaway token spend before tool calls.

Monitors AI agent actions, enforces permission boundaries, and automatically rolls back damage without code changes.

Security firewall for AI agents that intercepts tool calls and sends push notifications for approval decisions.

Provides a runtime boundary for AI agents to enforce access limits, inspect actions, and export signed evidence.

Provides runtime infrastructure for autonomous AI agents, including identity, permissions, audit logging, and governance.

Secures AI agents with a local-first runtime proxy to detect prompt injection and data exfiltration.

Provides an external pre-execution admission boundary to control automated and artificial intelligence actions.

Blocks unsafe AI agent actions before execution using versioned policy enforcement and verifiable chain-of-custody proofs.

Enables local, telemetry-free verification of AI agent actions against machine-verified system specifications.

Enables control over AI model calls, tool invocations, and agent actions before execution. It provides real-time policy enforcement with cryptographic evidence.

Blocks data leaks, prompt injection, and off-policy outputs for artificial intelligence applications with real-time alerts.

Provides an AI proxy for institutional memory and agent governance, enforcing runtime security policies and scoping access.

Provides runtime security and sandboxing for AI agents to dynamically adjust permissions as tasks change.

Secures AI agents with verifiable identity and enforces authorization decisions for every action across LLM and MCP traffic.

Provides generative AI agent guardrails mapped to MITRE ATLAS with deterministic tool-call boundary controls.

Provides secure runtime environments for AI agents using Firecracker sandboxes and built-in guardrails. It includes features like PII redaction, prompt injection defense, code security, toxicity scanning, and network…

Provides a secure vault for AI agents to access data with permission. Data is stored in a zero-knowledge vault, and redacted after each session.

Enforces policies, approvals, spend controls, and auditability across enterprise artificial intelligence applications and agents.

Provides an LLM security API to detect prompt injections, jailbreaks, harmful content, and personal data leaks.