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Evidently AI

company · United States

Scores

1 product on the map — 1 open.

Evidently

Openness

5 high confidence
5.0
license
Apache-2.0(OSI, single root LICENSE)
source
public(the full Monitoring UI service is self-hostable from this repository, per the README's own "Self-host the open-source version" option)
core features withheld
no — no ee/enterprise path in the recursive tree

Evidently is released under Apache-2.0 throughout, and both the evaluation library and the self-hostable monitoring dashboard are published in the same repository. Evidently Cloud adds dataset and user management, alerting and no-code evals on top of that open core, rather than withholding any of it.

Adoption

3 medium confidence
3.0

Adoption is measured by PyPI downloads of the evidently package, since installing it delivers the whole product: the evaluation library and the self-hostable Monitoring UI both ship from the same package, so the count is a direct measure of use rather than a proxy. GitHub stars on the project, active since 2020, corroborate without adding to the measurement.

Capability

3 high confidence
3.0

Evidently is a deep evaluation and monitoring library, with an unusually large set of built-in metrics and continuous monitoring as its main surface. Its monitoring reads metrics and test results computed over batches of data rather than live per-call tracing, which keeps it a step behind Langfuse.

  • https://raw.githubusercontent.com/evidentlyai/evidently/main/README.md recorded 2026-10-07

    Feature list: "100+ built-in metrics from data drift detection to LLM judges," Reports and Test Suites with pass/fail conditions, "Both offline evals and live monitoring," and a Monitoring Dashboard to "visualize metrics and test results over time" - no prompt-management or playground section anywhere in the document.