Openlayer
AI governance and observability for trust and control
À propos de Openlayer
Openlayer provides AI governance and observability tools to ensure reliable AI deployment. With automated testing, real-time guardrails, and compliance features, it helps teams build and monitor AI systems with confidence, from prototype to production.
Tarifs
Page de tarifs complèteOption gratuite
Basic
0 $US par mois
Trial ready to start for everyone
- Import your repo
- Test your AI in secs
- Automatic CI/CD
- Dozens of template projects
- AI test library
- Observability & tracing
- Alerting integrations
- 20k inferences / mo
- CLI, SDK, API access
- Community support
Enterprise
Sur mesure
Tailored for larger businesses
- All Basic plan features
- Team access controls
- Deploy on-prem
- Explainability
- SAML SSO
- 99.99% SLA
- White-glove onboarding
- Advanced support
- Trusted by top AI teams
FAQ
Openlayer provides 100+ automated tests and real-time guardrails to prevent issues like prompt injection, PII leakage, and hallucinations, ensuring secure and trustworthy AI systems.
Openlayer offers automated checks for data quality, including testing for schema changes, drift, and anomalies, to catch bad data before it affects your models.
Yes, Openlayer helps align AI systems with standards like ISO/IEC 42001, OWASP, NIST, and the EU AI Act for effortless governance and compliance.
Openlayer integrates with Git, provides SDKs for popular programming languages, and works with every LLM provider. It can be fully customized via a CLI and REST API.
Yes, Openlayer supports both ML and LLM systems, providing tools for evaluation, observability, and real-time monitoring across the entire AI lifecycle.
Openlayer allows teams to collaborate in a shared workspace, assign roles, define tests, and debug issues together, ensuring alignment across stakeholders.
Yes, Openlayer offers pre-configured templates for common AI patterns, such as chatbots, RAG pipelines, and structured outputs, to accelerate setup.
Openlayer provides real-time tracking, alerts, annotation, and tracing for all system requests, allowing teams to observe and monitor AI systems in production and fix issues quickly.
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