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End-To-End LLM Security Monitoring and Observability

Enable comprehensive security, governance, and monitoring of risks across all enterprise LLM applications.

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Deploy LLMs with Confidence

GenAI applications are being rapidly integrated into corporate environments. These applications are prone to unique security risks that are hidden from view and limit an enterprise's ability to secure their deployment and govern their use. A scalable solution is essential for security teams to provide comprehensive visibility and robust security monitoring to deploy GenAI with confidence.

Layer provides organizations with the necessary tools for detection and remediation to help prevent data leakage, adversarial prompt injection attacks, and integrity breaches so you can build, adopt, and deploy Large Language Models (LLMs) confidently.

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End-To-End LLM Security

Analyze LLM prompts, responses, data retrieval, and actions performed by the LLM beyond the prompt and output, by checking for security and compliance risks such as data leakage, adversarial prompt attacks, and other threats.

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Built for Enterprise Compliance

The “layered approach” allows you to configure as many guardrails and security checks as your enterprise AI Application needs. Built on top of learnings from LLM Guard, which has 4M+ downloads, the no-code workflows allow for efficient collaboration between security and AI teams, with built-in remediation guidance.

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Deploy on Any LLM Model

Efficiently secure and govern any large language model application, whether it's a vendor-managed model or a custom-built system, ensuring safe and compliant usage for all your generative AI deployments.

Purpose Built No Code Workflows for Security Teams

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Collect data on all LLM interactions and calls made up and downstream, so you can aggregate all your LLM applications across all deployment or usage patterns.

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Configure an extensive set of out-of-the-box security and governance policies to prevent data leakage, defend against adversarial prompts, and much more.

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Detect policy violations, with session-based investigations that include complete conversational content, and a granular review of each respective violation.

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Respond with built-in remediation guidance for detected violations and downstream integrations to task management, security incident management, and SIEM/SOAR tools, such as Splunk and Datadog.