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Confident AI

closed / Overall score: 3.5

Hosted platform layered on the DeepEval library, adding dataset management, regression tracking, human annotation, custom dashboards, online evaluations against live traffic, alerting and incident response. It also covers red teaming against adversarial attacks and AI governance, and gates CI so a build fails when quality drops below a defined threshold. Self-hosting into a customer VPC or on-premises is an enterprise option.

The scored entity is the hosted platform, not the separate DeepEval framework, which has its own record and whose openness is not credited here.

Openness

1 high confidence

1.0

license: proprietary(platform)
source: closed(platform)
note: companion OSS framework DeepEval is Apache-2.0 but is a separate registry-scope product
self-host: enterprise-tier

What is scored here is the Confident AI platform, which is proprietary SaaS. DeepEval, the open Apache-2.0 evaluation framework from the same team, is a distinct product, and the platform does not inherit its openness.

https://github.com/confident-ai/deepeval recorded 2026-08-13
The separate framework. GitHub resolves LICENSE.md to Apache-2.0 and the README states "DeepEval is licensed under Apache 2.0". This is the companion product, not the platform scored here.
https://www.confident-ai.com/ recorded 2026-09-29
Home FAQ: "Yes. Confident AI offers a fully self-hosted deployment option alongside the managed cloud." and "Self-hosting is available on our Enterprise plan". Searched the body for a source repository or license for the platform: none, only the DeepEval and DeepTeam frameworks are called "open-source".
https://www.confident-ai.com/docs/self-hosting recorded 2026-09-29
Self-hosting docs: "Self-hosting runs the entire Confident AI platform inside your own cloud account." and "to get a license key and access to the container images." so deployment needs a vendor license key and images. Searched for open source and source code: none.

Adoption

3 medium confidence

3.0

Confident AI's homepage cites more than 500 AI companies as customers but publishes no usage or user figures for the platform itself, so the reading reflects a disclosed claim rather than a measured count. Interest in DeepEval, the companion open-source framework that drives platform signups, corroborates the claim.

https://github.com/confident-ai/deepeval recorded 2026-08-13
17,578 stars on the DeepEval repository.
https://www.confident-ai.com/ recorded 2026-09-29
Homepage banner "TRUSTED BY 500+ LEADING AI COMPANIES" with community stats "14K+ STARS" and "2,500+ MEMBERS". No user or account count for the platform appears.

Capability

4 medium confidence

4.0

Confident AI's evaluation metric library, more than fifty DeepEval methods including G-Eval and LLM-as-judge, and its OWASP-aligned red-teaming layer stand out, but the platform's overall breadth keeps it level with Langfuse rather than ahead of the category's open-source tools.

https://www.confident-ai.com/ recorded 2026-09-29
Homepage FAQ: "DeepEval is our open-source evaluation framework for running LLM tests locally or in CI." Product menu: "Trace, monitor, and alert on production LLM systems." and "Stress-test LLM apps against adversarial attacks." and CI "you can run regression tests on every pull request".
https://www.confident-ai.com/docs recorded 2026-09-29
Docs home lists annotation queues, dataset management and red teaming sections; text reads "DeepEval is the open-source framework for evaluation and local tracing." and "Trace, monitor, and alert on production LLM systems."

Verified 2026-09-29