Confident AILLM evaluation platform built on DeepEval for testing, monitoring and improving AI applications.
Overview
Key features
- DeepEval-powered evaluation metrics
- Regression testing for prompts and models
- RAG and retrieval evaluation
- Production tracing and monitoring
- Dataset and test case management
- Team collaboration on evaluation results
Pricing
- Model
- Free
- Category
- Observability
- Rating
- 4.6 / 5 (5)
Use cases
Improving AI Quality
Confident AI provides a platform for testing, monitoring, and improving AI applications, allowing teams to validate quality and catch vulnerabilities before shipping.
Streamlining AI Governance
Confident AI offers a centralised eval standard, enabling teams to align to the same quality bar and reducing time to production.
Enhancing Agentic AI Security
Confident AI addresses top security risks for agentic AI applications, providing a comprehensive evaluation of vulnerabilities and attack vectors.
Pros & Cons
Pros
- Built on the widely used DeepEval open-source library
- Covers both pre-deployment testing and production monitoring
- Centralized dataset and prompt management
- Quantitative metrics for hallucination, relevance and more
Cons
- Primarily aimed at technical users familiar with LLM evaluation
- Learning curve to design meaningful test cases
- Value depends on integrating into existing dev workflows
Battle record
Across 3 battles in the Pantheon.
Last 3 battles
Reviews
Average from 5 ratings.
Sign in to leave a review.
Compared a few options
Evaluated this against two competitors. Where it wins: team collaboration on evaluation results and covers both pre-deployment testing and production monitoring. Where it lags: value depends on integrating into existing dev workflows. On balance the feature set — especially deepEval-powered evaluation metrics — justifies the 4 stars for our use case.
Years in this space
I've evaluated a lot of these over the years. What stands out here is rAG and retrieval evaluation — handled better than most — and built on the widely used DeepEval open-source library. Worth the time if this is your use case.
Does the job
Pretty happy overall. Dataset and test case management just works and quantitative metrics for hallucination, relevance and more. Value depends on integrating into existing dev workflows can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Compared a few options
Evaluated this against two competitors. Where it wins: production tracing and monitoring and quantitative metrics for hallucination, relevance and more. Where it lags: primarily aimed at technical users familiar with LLM evaluation. On balance the feature set — especially dataset and test case management — justifies the 5 stars for our use case.
Compared a few options
Evaluated this against two competitors. Where it wins: production tracing and monitoring and covers both pre-deployment testing and production monitoring. On balance the feature set — especially team collaboration on evaluation results — justifies the 5 stars for our use case.
Q&A
What is Confident AI?
Confident AI is the AI quality platform built by the creators of DeepEval. It gives engineering, QA, and product teams a single place to evaluate, observe, and improve LLM applications — from prototyping through production.
Asked by Devin Walker · May 12, 2026
How is Confident AI different from DeepEval?
DeepEval is our open-source evaluation framework for running LLM tests locally or in CI. Confident AI is the cloud platform that layers on top — adding collaboration, dataset management, tracing, real-time monitoring, and dashboards so the whole team can work together.
Asked by Freya Solberg · Apr 24, 2026
Does Confident AI offer LLM observability?
Yes. Every LLM call is captured as a trace with full context — inputs, outputs, tool calls, latency, token cost, and metadata. You can drill into any production request, set up alerts on quality degradation, and monitor trends over time without building custom logging.
Asked by Kwabena Asante · Apr 9, 2026
Can I use Confident AI in CI/CD pipelines?
Yes. DeepEval integrates directly into your CI pipeline so you can run regression tests on every pull request. If quality drops below thresholds you define, the build fails — no bad prompts make it to production.
Asked by Wanjiru Kamau · Feb 22, 2026
Can I self-host Confident AI?
Yes. Confident AI offers a fully self-hosted deployment option alongside the managed cloud. You can run the entire platform in your own VPC or on-prem infrastructure, keeping all data within your network. Self-hosting is available on our Enterprise plan — book a demo to get started.
Asked by Urszula Kowalczyk · Feb 24, 2026
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