Openlayer
Openlayer helps AI teams monitor, test, and validate model outputs in real time. Track performance, detect issues, and improve reliability across deployments with seamless Git and SDK integration.
About Openlayer
Infrastructure for Safe and Scalable AI Deployment
Openlayer is a comprehensive platform for evaluating, testing, and monitoring AI models in production. It empowers development teams to surface issues early, ensure consistent output quality, and maintain trust across environments—whether in startups or large enterprises.
Trusted by Leading AI Teams
Openlayer is used by top organizations to deploy AI with confidence. By offering advanced observability and test creation tools, the platform enables teams to accelerate their deployment cycles without compromising on model safety or output reliability.
AI Model Testing Made Simple
Real-Time Output Evaluation
With Openlayer, teams can create and run tests on live model responses, verifying metrics like answer correctness, bias prevention, latency, and the presence of personally identifiable information (PII). Tests are fully customizable and can be adapted to any AI task or product.
Trace and Debug with Human Feedback
Developers can annotate model outputs, add human feedback, and trace requests end-to-end. This allows quick identification of error patterns, helping teams move faster from issue discovery to resolution.
Performance Monitoring and Deployment Insights
Monitor Across Environments
Openlayer supports monitoring across development and production environments, giving visibility into how models behave under different real-world scenarios. It tracks success metrics like response time, token usage, and model accuracy at scale.
Validate Key Objectives with Prebuilt Metrics
Predefined goals—such as relevancy thresholds, response structure, and fairness scoring—ensure every AI release meets organizational standards. Openlayer includes checks for harmful outputs, discrimination, and context precision.
Built for Collaboration and Integration
Streamlined Team Workflows
Teams can assign roles, share results, and debug together within a shared workspace. All testing activity is logged and organized, enabling aligned collaboration across engineering, research, and QA teams.
Integrated with Your Stack
Openlayer works seamlessly with Git, offers REST APIs and CLI tools, and supports popular SDKs. Whether you're using OpenAI, LangChain, Claude, or custom LLMs, Openlayer fits smoothly into any development workflow.
Templates and Use Cases
Ready-to-Use AI Testing Pipelines
Openlayer offers templates for various use cases including resume screening, chatbot QA, RAG pipelines, and structured outputs. These jumpstart testing for projects in finance, e-commerce, recruiting, healthcare, and beyond.
Case Studies from Leading Companies
Companies using Openlayer report faster deployment cycles, improved model accuracy, and reduced debugging time. By integrating real-time testing into CI/CD workflows, they unlock higher throughput and maintain better model reliability.