Runtime security for your AI apps and agents, everywhere they run
Block data leakage, model poisoning and rogue agents in real time, across public, private and hybrid clouds and the edge, without slowing down your AI.
AI is moving faster than your security model
Sensitive data, API keys and secrets flow into models and third-party AI platforms with no visibility into where they go.
Poisoned data and malicious MCP tools can quietly change how your AI behaves.
Autonomous agents with too much access can act outside their intended boundaries, and traditional security tools weren't built to stop them.
Everything you need to secure AI at runtime
Runtime defense that goes beyond Kubernetes to public, private and hybrid clouds, agentic workflows and edge environments, including large data platforms and LLM and agent platforms.
Cross-platform threat modeling with out-of-the-box OWASP mappings for sensitive data leakage, secrets leakage, prompt injection and data poisoning, plus the exact workloads and APIs affected.
Detect and block unauthenticated or unauthorized agents, map trust scores across your agent supply chain and enforce least-privilege execution.
Protect both the runtime and API access layers of MCP-based agent tools, with identity and access controls built for AI NHIs.
One control point between your AI and every model it calls
AI Gatekeeper sits between your APIs, applications, agents and containers and the models they use, whether cloud AI APIs like OpenAI, Amazon Bedrock and Gemini or internal models like Cohere, Hugging Face and Llama. Every request is inspected, redacted or blocked in real time.
Get a live, auto-updating catalog of every AI workload, agent, tool, model and platform in use, including OpenAI, Anthropic, Hugging Face, Cohere, DeepSeek and more.
See your highest-risk data flows between workloads, agents and AI APIs on a single AI Security Graph, mapped to the OWASP Top 10 for LLMs and AI Agents.
Allow, redact or block in real time, from ingress to egress, with defense analytics showing exactly what was stopped.
Security that keeps your AI working
Most AI security forces a trade-off between protection and functionality. AI Gatekeeper redacts private data in-line, so sensitive information never leaves your environment while your models and applications keep working at full capability. Least-privilege controls cover APIs, containers and agents, making your AI ecosystem secure by default.
Extend protection across your entire MCP ecosystem
AI Gatekeeper secures MCP tools in your runtime. Pair it with Operant MCP Gateway for real-time visibility and control over MCP across endpoints and cloud.
Learn about MCP Gateway
FAQ
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Allow it, clean it, or block it, before the action goes through.