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Openlayer

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Governance e osservabilità dell’IA per testare, monitorare e controllare sistemi ML e LLM

Cos'è Openlayer?

Openlayer is an AI governance and observability platform for evaluating, monitoring, and controlling ML and LLM systems. The product combines offline evaluation, production tracing, live guardrails, and automated compliance workflows so teams can test systems before release and watch them in production.

The site positions Openlayer for builders working on GenAI apps, agents, copilots, retrieval-augmented generation, and traditional ML models. It supports structured testing, request tracing, data quality checks, and compliance alignment with standards such as NIST, ISO/IEC 42001, OWASP, and the EU AI Act.

Cosa può fare Openlayer?

Automated model testing

Run more than 100 built-in and customizable tests to evaluate hallucination, completeness, relevance, toxicity, bias, and other output qualities.

Version and change comparisons

Compare prompts, model providers, and system changes to spot regressions and track improvements over time.

Production observability

Trace prompts, tool calls, intermediate steps, responses, latency, and cost across LLM pipelines and agent workflows.

Real-time guardrails and alerts

Run live safety and performance checks and set alerts for issues such as prompt injection, data leaks, latency spikes, and inappropriate content.

CI/CD and workflow integration

Use SDKs, APIs, CLI workflows, GitHub Actions, and Git-based processes to trigger tests as part of development and deployment.

Collaborative evaluation

Support shared review and feedback across engineers, product managers, researchers, and other stakeholders in a single workspace.

Casi d'uso

“Pre-release model evaluation”

Evaluate prompts, model outputs, and release candidates before shipping by using test suites, comparisons, and LLM-as-a-judge scoring to catch regressions early.

“Production observability”

Monitor live GenAI systems for prompt injection, toxic output, data leaks, latency, and cost issues, then investigate failures with full request traces.

“Data quality monitoring”

Run automated checks on incoming data to detect schema changes, drift, and anomalies before bad data reaches models.

“Cross-functional review”

Coordinate review among engineers, PMs, researchers, and other stakeholders with shared evaluation results, comments, and comparison workflows.

“Governance and compliance workflows”

Align AI systems with governance and compliance frameworks by using testing and monitoring workflows that support standards such as NIST, ISO/IEC 42001, OWASP, and the EU AI Act.

Domande frequenti

How do you evaluate models in Openlayer?

Openlayer supports structured testing for LLMs and ML models, including LLM-as-a-judge scoring, rubric-based evaluation, prompt test coverage, and comparisons across versions or prompts.

What tools and frameworks does Openlayer integrate with?

The source pages state support for OpenAI, Anthropic, Hugging Face, LangChain, OpenTelemetry, Snowflake, GitHub Actions, GitLab CI, and more, depending on the workflow and product area.

What can you monitor or trace in production?

Openlayer can trace prompts, tool calls, latency, cost, model responses, and failure modes across multi-step and retrieval-based workflows.

Does Openlayer offer both self-serve and enterprise plans?

The pricing page shows a Basic trial plan and an Enterprise plan. Basic includes 20,000 inferences per month, CLI/SDK/API access, and community support, while Enterprise adds options such as team access controls, on-prem deployment, explainability, SAML SSO, and white-glove onboarding.

Informazioni rapide

Category
AI governance and observability
Primary users
Builders working on GenAI apps, LLM systems, and ML models
Deployment model
Cloud platform with enterprise on-prem option
Pricing
Basic trial and Enterprise plans listed
Source domain
openlayer.com
Workflow
Offline evaluation, production monitoring, and compliance tracking

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Domain Rating
56

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