AI agent security platform providing guardrails, prompt injection detection, and content filtering for production agent deployments.
Security guardrails for AI agents — protects against prompt injection, data leaks, and other AI-specific attacks.
Keeper AI is a security platform designed specifically for protecting AI agents in production. As autonomous agents gain more capabilities — tool access, code execution, data retrieval, and external API calls — the attack surface expands dramatically. Keeper AI provides the security guardrails that prevent prompt injection, data exfiltration, unauthorized actions, and harmful outputs.
The platform operates as a middleware layer between your agent and the outside world. Every input to and output from the agent passes through Keeper's security pipeline, which applies configurable rules, ML-based threat detection, and policy enforcement. This architecture means you can add security to any existing agent without modifying its core logic.
Prompt injection detection is a core capability. Keeper uses multiple detection methods — pattern matching, semantic analysis, and trained classifiers — to identify attempts to manipulate agent behavior through crafted inputs. When an injection attempt is detected, the platform can block the request, sanitize the input, or alert operators while allowing the request through.
The policy engine lets teams define rules about what agents can and cannot do. These policies can restrict which tools agents can call, what data they can access, what content they can generate, and which external services they can contact. Policies are defined declaratively and can be updated without redeploying agents.
Content filtering covers both inputs and outputs, detecting and blocking PII exposure, harmful content, off-topic responses, and confidential information leakage. The system provides configurable sensitivity levels to balance security with usability.
Keeper includes an audit log capturing every agent action, policy decision, and security event. This is essential for compliance in regulated industries and for post-incident analysis. The dashboard provides real-time visibility into security events, policy violations, and threat patterns.
For organizations deploying agents that handle sensitive data, interact with customers, or have access to business-critical tools, Keeper AI provides the security layer that makes the difference between a prototype and a production-ready deployment. Its agent-specific focus means it understands threats unique to AI agents that traditional security tools miss.
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Multi-method detection combining pattern matching, semantic analysis, and ML classifiers to identify manipulation attempts.
Use Case:
Blocking a customer support agent from being tricked into revealing system prompts or internal data.
Declarative rules defining what agents can do — tool restrictions, data access controls, content boundaries, and action limits.
Use Case:
Restricting a sales agent from accessing customer payment information or calling external APIs not on the allowlist.
Automatic detection and redaction of personally identifiable information in both agent inputs and outputs.
Use Case:
Preventing an agent from including customer email addresses or phone numbers in logged conversations.
Configurable filtering for harmful content, off-topic responses, and confidential information with sensitivity controls.
Use Case:
Ensuring a public-facing agent stays on topic and doesn't generate inappropriate or legally risky content.
Comprehensive logs of every agent action, policy decision, and security event for compliance and incident analysis.
Use Case:
Providing regulators with a complete audit trail of agent decisions in a financial services application.
Deploys as a layer between agents and the world, adding security without modifying agent code or logic.
Use Case:
Adding security guardrails to an existing LangChain agent by routing requests through Keeper's proxy.
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Regulated industry compliance
Enterprise agent security
Multi-agent system governance
We believe in transparent reviews. Here's what Keeper AI doesn't handle well:
Keeper adds 50-150ms per request for security analysis. For real-time chat applications this is generally acceptable; for latency-critical pipelines, async mode is available.
No security system is 100% effective. Keeper provides defense-in-depth with multiple detection methods, significantly reducing risk. It should be part of a broader security strategy.
Yes, Keeper operates as HTTP middleware that works with any agent framework — LangChain, CrewAI, custom agents, or direct LLM API calls.
Yes, Keeper's audit logging, PII detection, and policy engine are designed for compliance requirements in financial services, healthcare, and other regulated sectors.
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