Why Evidently?

We’re building Evidently AI to help teams ship reliable AI products: whether it’s an ML model, an LLM app, or a complex agent workflow.

Our tools are model-, framework-, and application-agnostic, so you can build and evaluate AI systems your way without limitations.

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We are open-source

Evidently is an open-source library with over 25 million downloads, 5000+ GitHub stars, and a thriving community. It’s licensed under Apache 2.0. This gives full transparency - you can see exactly how every metric works and trust the implementation. It also delivers an intuitive API designed for a great developer experience.

The Evidently Platform builds on the library with additional UI features and workflows for team collaboration. For enterprise users, we offer both Cloud and self-hosted options for full data privacy and control.

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Evidently is very modular 

Evidently is built to adapt to your needs without lock-ins or complex setups. It’s modular and component-based, so you can small: you don’t have to deploy a service with multiple databases just to run a single eval.

• Start with local ad hoc checks. 

• Want to share results? Add a UI to track evaluations over time. 

• When you run evals, choose to upload raw data or only evaluation results. It’s up to you. 

• Add monitoring as you are ready to move to production workflows.

Evidently integrates with your existing tools and lets you easily export metrics, reports, and datasets elsewhere. 

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100+ built-in evaluations

Evidently puts evaluations first. 

Many other tools provide a system to run and log evals, but expect you to implement all the metrics from scratch. We ship 100+ built-in evaluations that cover many ML and LLM use cases. From ranking metrics to data drift algorithms and LLM judges, we’ve done the hard work by implementing metrics and ways to visualize them.  

Evidently is built around the concept of Presets and reasonable defaults: you can run any check with minimal setup, including with auto-generated test conditions for assertions.

We also combine ready-made evaluations with the flexibility to create your own. You can easily extend Evidently using templates and the custom metric API to add your checks.

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Complete feature set

Why evals are core, Evidently Platform offers a comprehensive feature set to support AI quality workflows: with tracing, synthetic data generation, rich dashboard, built-in alerting etc.

Get the Platform overview.

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Loved by community

Thousands of companies, from startups to enterprises, use Evidently. Check some of our reviews.

We’re also known for openly sharing knowledge that helps developers succeed. Check out resources like LLM evaluation course, open-source ML observability course, guides, and blogs.

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Handles both ML and LLM 

Evidently supports both ML and LLM tasks. We believe this matters even if you’re focused solely on LLMs and not training your models.

Real-world AI systems are rarely just one thing, and two types of workflows overlap. For example:

• an LLM-based chatbot may need classification steps like detecting user intent.

• if you are building with RAG, you are solving a ranking problem first.

Evidently Platform can support both complex nested workflows and structured tabular data, and has relevant metrics and views for both. This means you’re won’t be locked into a single approach - or have to reinvent the wheel to measure things like Hit Rate or Precision over traces.

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Built for collaboration

Evidently started as an open-source project loved by data scientists and AI/ML engineers. But we’re building more than a developer tool - we’re building a platform where domain experts and engineers can work together easily.

Reliable AI systems require teams to work together: on curating test data, gathering feedback, and running evaluations. We build our platform with this in mind: combine no-code workflows for non-technical users with an intuitive API. Everyone gets what they need to do their best work.

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Trusted partner 

Founded in 2021, Evidently AI is built by a team with 10+ years of experience deploying AI in high-scale, critical scenarios. We are backed by world-class investors like Y Combinator, Fly Ventures, Runa Capital, Nauta Capital and angel investors. Our core Evidently library a stable history of development and earned trust from the community and enterprise users alike.