Evidently AI
AI Evaluation & LLM Observability Platform.
Overview
Evidently AI is an open-source framework for ML and LLM observability. It provides a rich set of tools to analyze and track data quality, data drift, and model performance. Evidently generates interactive visual reports and provides a declarative testing API to formalize model quality checks. It can be used as a Python library or as part of the Evidently Cloud platform for a complete observability solution.
✨ Key Features
- Comprehensive data and model evaluation (100+ metrics)
- Data drift and model drift detection
- Interactive visual dashboards
- Declarative testing API for model validation
- LLM evaluation and monitoring
- Open-source Python library
- Managed cloud platform available
🎯 Key Differentiators
- Strong open-source offering with a large user base
- Rich set of pre-built tests and visual reports
- Focus on both evaluation during development and monitoring in production
Unique Value: Provides a powerful, open-source, and developer-friendly way to evaluate, test, and monitor data and ML models throughout their lifecycle.
🎯 Use Cases (5)
✅ Best For
- Automated data drift detection in CI/CD pipelines
- Generating model performance reports for stakeholders
- Interactive debugging of model degradation
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Users looking for a no-code, purely UI-driven platform
- Organizations that need a unified platform for full-stack application and infrastructure monitoring
🏆 Alternatives
Offers a more comprehensive set of pre-built evaluations and reports than other open-source libraries. It is more focused on data and model quality than general-purpose pipeline orchestrators.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Live Chat
- ✓ Dedicated Support (Cloud tier)
🔒 Compliance & Security
💰 Pricing
✓ 14-day free trial
Free tier: Open-source is free forever
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