Evidently AI
Open-source evaluations and observability for LLM apps
Listed in categories:
Artificial IntelligenceOpen SourceDeveloper Tools
Description
Evidently is an open-source AI observability platform designed to evaluate, test, and monitor AI-powered products, particularly those based on LLMs (Large Language Models). It provides a comprehensive toolkit for ensuring the quality and performance of machine learning models throughout their lifecycle, from development to production.
How to use Evidently AI?
To use Evidently, start by integrating it with your AI models and data pipelines. You can run ad hoc tests on sample data, transition to continuous monitoring once your AI product is live, and utilize customizable dashboards to visualize performance metrics. The platform allows for both programmatic checks and web interface usage, making it flexible for different team needs.
Core features of Evidently AI:
1️⃣
AI quality toolkit for development and production
2️⃣
Customizable dashboards for performance visibility
3️⃣
Continuous testing and evaluation of AI outputs
4️⃣
In-depth debugging and error analysis
5️⃣
Data drift detection and monitoring
Why could be used Evidently AI?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Monitoring production data for AI models | ✅ | |
| # 2 | Evaluating model performance and data quality | ✅ | |
| # 3 | Detecting anomalies and ensuring compliance with guidelines | ✅ | |
Who developed Evidently AI?
Evidently is developed by a community of ML and AI engineers, with a focus on providing a robust and user-friendly tool for monitoring machine learning models. The platform is built on the leading open-source ML monitoring library, ensuring transparency and extensibility for users.