📄️ Key Concepts
Learn about the key concepts behind WhyLabs Secure, and how it can help you protect your AI applications.
📄️ Feature Walkthrough
An overview of the features available in WhyLabs Secure
📄️ Guardrail Metrics
Overview
📄️ Guardrails API
As part of the WhyLabs Secure solution, the Guardrails API is a RESTful API that allows you to interact with the WhyLabs Guardrails service. This powerful tool enables organizations to implement robust safety measures and control mechanisms for their AI and ML systems, particularly for Large Language Models (LLMs).
🗃️ WhyLabs Secure Policy
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📄️ openLLMtelemetry
openLLMtelemetry is a package built on top of OpenTelemetry
📄️ Integration: OpenAI
Integration with an OpenAI application is straightforward with openllmtelemetry package.
📄️ Integration: Amazon Bedrock
Integration with an Amazon Bedrock application is straightforward with openllmtelemetry package.
📄️ Integration: Azure OpenAI
Integration with an Azure OpenAI application is straightforward with openllmtelemetry package.
📄️ Integration: NVIDIA NIM
NVIDIA NIM is a platform for managing and deploying AI models APIs that are compatible with the OpenAI client.
📄️ Integration: IBM watsonx
IBM® watsonx™ AI and data platform includes three core components and a set of AI assistants
🗃️ Deployments
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📄️ Benchmarks
This benchmark shows the result of the WhyLabs Secure solution on various datasets.
🗃️ LangKit
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📄️ OWASP top 10 for LLM Security
The dynamically developing field of LLM applications introduces new kinds of vulnerabilities. These emerging threats were summarized into 10 risk categories by the OWASP Foundation, a non-profit organization aiming at democratizing and standardizing software security.
📄️ Data Security and Privacy
WhyLabs Secure is designed with a strong emphasis on data security and privacy, particularly for organizations handling sensitive information in their AI applications. Several key aspects of its architecture contribute significantly to maintaining the confidentiality and integrity of LLM data.
