Evidently AI - Open-Source ML Monitoring and Observability

🚀 Enhance your ML monitoring game with Evidently AI! 🤖⚙️ From data quality to model performance, this open-source tool is a data scientist's dream. 💻🔍 Monitor with ease and precision! #AI #ML #DataScience #MLOps

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The ML observability platform supports monitoring ML models from validation to production.
It caters to data scientists and ML engineers.
It provides an all-in-one tool for running ML systems in production.
Users can start with simple ad hoc checks and scale up to a complete monitoring platform.
The platform offers useful, beautiful, and shareable reports for data and ML model quality.
It facilitates testing pipelines, monitoring data, models, and test results.
Users can track data quality, drift, model performance, LLM, and NLP with over 100 metrics.
The platform is used by data scientists and ML engineers for support and collaboration in Discord.
Testimonials from various professionals endorse the tool for monitoring ML models.
Evidently simplifies model monitoring with preset tests and metrics.
It offers flexibility to customize tests, metrics, and reports.
Evidently helps in debugging machine learning models.
The platform allows users to turn predictions to metrics and metrics to dashboards.
Users can visualize and explore data over time on monitoring dashboards.
Evidently is available as Evidently Cloud for easy setup or as open-source for self-deployment.
The platform uses the Evidently Python library for logging snapshots and capturing metrics.
Evidently enhances the user experience of MLOps platforms and expedites provisioning for monitoring models in production.