Confident AI Overview
Confident AI is a comprehensive LLM Evaluation and Observability Platform, developed by the creators of the popular open-source library DeepEval and backed by Y Combinator. It is specifically designed for engineering teams to systematically benchmark, safeguard, and enhance their Large Language Model (LLM) applications. The platform provides an end-to-end solution for managing the entire LLM lifecycle, from development and testing to production monitoring, ensuring that AI systems are reliable, cost-effective, and continuously improving.
By integrating best-in-class metrics and advanced tracing capabilities, Confident AI empowers teams to move beyond anecdotal evidence and make data-driven decisions. It helps prevent performance regressions, optimize prompts and models, and provides clear, actionable insights for both technical and non-technical stakeholders. The platform is trusted by leading companies and has a strong open-source community, performing hundreds of thousands of evaluations daily.
How to use Confident AI
Setting up and using Confident AI is a streamlined, developer-first process that can be completed in minutes:
- Install DeepEval: The first step is to install the open-source DeepEval library into your existing development environment, regardless of the framework you are using. The command is a simple `pip install deepeval`.
- Choose Metrics: Select from over 30 pre-built, LLM-as-a-judge metrics tailored to your specific use case, such as RAG evaluation, summarization, or answer relevancy. You can also create custom metrics to fit unique requirements.
- Plug It In: Integrate evaluations directly into your code by using a simple decorator (`@observe`) on your LLM application function. This allows you to apply your chosen metrics and configure test cases programmatically.
- Run an Evaluation: Execute your evaluation script to generate detailed test reports. These reports help you catch regressions in your CI/CD pipeline, and you can use the integrated tracing observability to dissect and debug individual components of your LLM pipeline, pinpointing weaknesses and areas for improvement.
Core Features of Confident AI
- End-to-End Evaluation: Measure and compare the performance of different prompts, models, and configurations to identify the optimal setup for your application.
- Regression Testing: Implement automated unit tests in your CI/CD pipelines to mitigate LLM regressions, ensuring that new changes don't break existing functionality and allowing for confident deployments.
- Component-Level Evaluation with Tracing: Dissect your LLM pipeline into individual components (e.g., retrieval, generation) and apply tailored metrics to each. Tracing provides deep visibility to debug and iterate effectively.
- DeepEval Integration: Built on the robust and widely adopted DeepEval open-source library, offering a familiar and powerful foundation for developers.
- Dataset and Prompt Management: Includes a cloud-based dataset editor for curating and annotating evaluation datasets, as well as tools for versioning and managing prompts.
- Enterprise-Grade Security & Compliance: Offers HIPAA and SOC2 compliance, multi-data residency options (US and EU), role-based access control (RBAC), data masking, and options for on-premise hosting.
- No-Code Prompt Playground: An intuitive interface for non-technical team members to experiment with and evaluate prompts without writing code.
Use Cases for Confident AI
Confident AI is versatile and supports a wide range of LLM applications, including:
- Retrieval-Augmented Generation (RAG) Systems: Evaluate the quality of retrieved context, the faithfulness of the generated answer to the context, and overall answer relevancy.
- LLM Chatbots & Virtual Assistants: Test for conversational quality, task completion, safety, and consistency across multi-turn dialogues.
- LLM Agents: Assess agentic reasoning, tool usage, and the ability to complete complex, multi-step tasks.
- Cost Optimization: By comparing different models and prompts, teams can identify configurations that meet performance requirements while cutting inference costs by up to 80%.
- Stakeholder Alignment: Generate clear, shareable reports that demonstrate AI performance improvements over time, convincing stakeholders and justifying product decisions.
Advantages of Confident AI
The platform offers significant advantages for teams building with LLMs:
- Time and Cost Savings: Automates the tedious process of manual evaluation, saving teams hundreds of hours per week and reducing unnecessary inference costs.
- Increased Confidence: Enables teams to deploy changes, even on Fridays, with the confidence that regressions will be caught automatically.
- Developer-Friendly & Team-Accessible: While built for developers with code-first integration, its intuitive dashboards and no-code tools make insights accessible to product managers and other team members.
- Trusted & Open-Source: Leverages the credibility and active community of DeepEval, ensuring a reliable and continuously improving evaluation framework.
- Secure & Scalable: Provides enterprise-ready features for security, compliance, and scalability, including on-premise deployment for maximum data control.
Pricing and Plans
Confident AI offers a tiered pricing structure to scale with your needs:
- Free: A forever-free plan for individuals exploring the platform. It includes DeepEval testing reports, LLM tracing, and prompt versioning, limited to 1 project, 5 test runs per week, and 1-week data retention.
- Starter (from $19.99/user/month): Designed for teams proving ROI. Includes everything in Free, plus a full unit/regression testing suite, custom metrics, human-in-the-loop feedback, and email support. Starts with 20k LLM traces/month and 1-month data retention.
- Premium (from $139.99/user/month): For teams shipping mission-critical products. Includes everything in Starter, plus online performance alerting, dataset revision history, multi-turn simulation, a no-code prompt playground, and a dedicated support channel. Starts with 75k LLM traces/month and 6-months data retention.
- Enterprise (Custom Pricing): For high-scale, security, and compliance needs. Includes everything in Premium plus unlimited users, projects, and traces, on-prem deployment, SSO, SOC2, dedicated 24/7 support, and custom integrations.
Traffic
Latest traffic
Status
Monthly traffic trend
- 2025-9: 97.9K
- 2026-1: 120.2K
- 2026-2: 127.9K
- 2026-3: 127.5K
- 2026-4: 127.6K
- 2026-5: 101.6K
Geography
Top 5 countries / regions
- 🇮🇳India32.6%
- 🇺🇸United States29.2%
- 🇹🇭Thailand14.6%
- 🇻🇳Vietnam12.8%
- 🇩🇪Germany10.8%
Traffic sources
| Source type | Percentage |
|---|---|
Direct | 84.8% |
Referral | 14.8% |
Email | 0.5% |
Top keywords
| Keyword | Cost per click |
|---|---|
| confident ai | $5.23 |
| deepeval | $4.67 |
| llm arena | $2.54 |
| llm as a judge | $2.50 |
| llm as judge | $3.90 |
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