概览
主要功能
- DeepEval 驱动的评估指标
- 提示和模型的回归测试
- RAG 与检索评估
- 生产追踪与监控
- 数据集和测试用例管理
- 团队协作评估结果
价格
- 模型
- Free
- 分类
- 标做管球解析
- 评分
- 4.6 / 5 (5)
使用场景
提升 AI 质量
Confident AI 提供一个用于测试、监控和改进 AI 应用的平台，使团队能够在发布前验证质量并捕获漏洞。
简化 AI 治理
Confident AI 提供统一的评估标准，使团队能够对齐相同的质量基准，减少投产时间。
增强 Agentic AI 安全性
Confident AI 解决 Agentic AI 应用的主要安全风险，提供对漏洞和攻击向量的全面评估。
优点 & 缺点
优点
- 基于广泛使用的 DeepEval 开源库构建
- 涵盖部署前测试和生产监控
- 集中式数据集与提示管理
- 提供幻觉、相关性等量化指标
缺点
- 主要面向熟悉 LLM 评估的技术用户
- 设计有意义的测试用例有学习曲线
- 价值取决于与现有开发工作流的集成
对决战绩
在万神殿中参与了 3 对决。
Last 3 battles
评测
5 个评分的平均值。
登录以留下评测。
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.
问答
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
提问
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