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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…

Monitors artificial intelligence spending and protects against unauthorized costs across multiple providers and agents.

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

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

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

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

Provides identity management, API key vaulting, usage limits, call logging, and a kill switch for AI agents.

Provides runtime security for artificial intelligence agents by screening tool results and documents.

Provides automated quality assurance, security guardrails, and token intelligence tools for prompts and AI agents.

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

Checks AI agent actions against defined rules to allow, pause for review, or block them.

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

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

Enables developers to define and verify authority for AI agents before actions execute.

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

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

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

Provides change control for artificial intelligence agents by requiring human approval before irreversible actions occur.

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

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

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

Manages AI agent access to SaaS tools with human approval, encrypted credentials, and audit logging.

Secures AI agents by mapping tool usage, minting capability tokens, and enforcing runtime policies.

Monitors, authorizes, and prices tool and model calls made by coding agents.

Controls and filters actions performed by artificial intelligence applications across connected accounts.

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

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

Manages authorization for AI systems, controlling actions like prompt execution and API requests. It evaluates policies in under one millisecond, returning allow, deny, redact, or hold. Decisions are recorded in a…

Manages billing and spending caps for artificial intelligence applications across multiple frontier models.