Freemium
Leading digital analytics platform for product insights and customer journey analytics
analyticsproduct analyticscustomer insights
View detailsKey facts
Pricing
Freemium
Use cases
Software engineers and QA teams running unit and regression tests to catch breaking changes before production deployment (verified: 2026-01-29), Product managers using analytic dashboards to evaluate RAG pipelines and agentic workflows without writing code (verified: 2026-01-29), Developers monitoring live LLM applications to track latency, cost, and error rates with real-time production alerts (verified: 2026-01-29)
Strengths
The platform provides over 30 LLM-as-a-judge metrics through the DeepEval framework to benchmark system performance (verified: 2026-01-29), Users can deploy the platform on-premises via Docker to maintain data control within AWS, Azure, or GCP environments (verified: 2026-01-29), The system supports human-in-the-loop feedback allowing team members to annotate datasets and leave feedback on the UI (verified: 2026-01-29)
Limitations
The Free Forever plan restricts users to one project and five test runs per week with one week of data retention (verified: 2026-01-29), Access to custom metrics and full LLM unit testing suites requires a paid Starter or Premium subscription (verified: 2026-01-29)
Last verified
Jan 29, 2026
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Strengths
- The platform provides over 30 LLM-as-a-judge metrics through the DeepEval framework to benchmark system performance (verified: 2026-01-29)
- Users can deploy the platform on-premises via Docker to maintain data control within AWS, Azure, or GCP environments (verified: 2026-01-29)
- The system supports human-in-the-loop feedback allowing team members to annotate datasets and leave feedback on the UI (verified: 2026-01-29)
Limitations
- The Free Forever plan restricts users to one project and five test runs per week with one week of data retention (verified: 2026-01-29)
- Access to custom metrics and full LLM unit testing suites requires a paid Starter or Premium subscription (verified: 2026-01-29)
FAQ
What specific metrics does Confident AI use to evaluate the performance of Large Language Models?
The platform utilizes the DeepEval framework which includes over 30 LLM-as-a-judge metrics. These metrics allow developers to benchmark LLM systems, catch regressions, and debug performance issues through detailed test reports and traces (verified: 2026-01-29).
Can organizations with strict data privacy requirements host the Confident AI platform on their own infrastructure?
Yes, organizations can deploy Confident AI in their own cloud premises, such as AWS, Azure, or GCP, using a dockerized setup. This on-premises hosting option includes integrations with identity providers like Azure AD, Ping, and Okta for secure authentication (verified: 2026-01-29).
How does the platform support collaboration between technical and non-technical team members during the evaluation process?
Confident AI provides intuitive product analytic dashboards designed for non-technical members like product managers. While engineers integrate evaluations using code, other team members can use the dataset editor, manage prompts, and provide human-in-the-loop feedback (verified: 2026-01-29).
