Evidently AI: Your Open-Source ML Observability Platform
Empower your ML workflows with Evidently, the open-source tool for evaluating, testing, and monitoring machine learning models. Designed for data scientists and ML engineers, supporting tabular data to NLP and LLM.
Features
- Self-Hosted ML Dashboard: Build and maintain your own ML monitoring dashboard with ease.
- Comprehensive Reporting: Generate beautiful, detailed reports for data and model quality insights.
- Pre-Production Testing: Validate models before shipping and with each update to ensure robust performance.
- Holistic Monitoring: Track every facet of your data and models to proactively manage issues and optimize performance.
- 100+ Integratable Metrics: Employ over 100 metrics to understand, visualize, and maintain data and model quality.
Use Cases:
- Data Quality Assurance: Automatically spot and correct data quality issues such as nulls, duplicates, and compliance with KPIs.
- Data Drift Detection: Identify changes in data distributions and adapt to model drift without manual labels.
- Model Performance Tracking: Monitor performance, uncover deviations and enhance model reliability in the real world.
- NLP and LLM Model Monitoring: Keep an eye on complex text-based models and manage unstructured data effectively.
Join a thriving community of 2,500+ members and elevate your ML systems with Evidently's comprehensive toolkit. Get started with quick integration and scale from ad hoc checks to a complete observability platform.
Evidently AI Alternatives:
1. Deepchecks Testing Package
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2. Censius
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4. Prompt Art
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5. Sagify
Command-line tool simplifying ML model training and deployment on AWS SageMaker.
7. Empy
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