Confident AI - AI Quality Platform for Evals and Observability

Whether you are building RAG pipelines, agentic workflows, chatbots, or fine-tuning models, Confident AI gives engineers, QAs, PMs, and domain experts the tools to measure, improve, and maintain AI quality across the entire application lifecycle.

## Key Capabilities

### Experimentation in Development

• Call your application via HTTPS or prompts to rapidly iterate and evaluate changes
• Compare prompts, models, and parameters to find the best configuration
• Run 40+ metrics to measure quality across functionality and safety
• Integrate automated evals into your CI/CD pipeline to catch regressions pre-deployment
• Establish quality gates that prevent degraded AI from reaching users

### Tracing and Online Evals in Production

• Trace every AI execution end-to-end with spans capturing inputs, outputs, latency, and tokens
• Run online evaluations to score production traffic in real-time
• Debug issues with complete context and identify quality regressions
• Build datasets from real user interactions for systematic testing
• Receive instant alerting when AI quality degrades

### Red Teaming for Security

• Test for safety vulnerabilities and harden your AI against adversarial attacks
• Apply frameworks, policies, and risk profiles to assess AI robustness
• Detect threats at the trace level in production

### Human-in-the-Loop Workflows

• Collect feedback and manage annotation queues
• Enable SMEs and annotators to label data and review AI outputs at scale
• Combine human judgment with automated metrics for comprehensive quality assessment

## Who Uses Confident AI

• **Engineers** - Unit-test AI apps in CI/CD, debug with traces, experiment with prompts and models
• **QAs** - Build test datasets, run regression suites, validate AI behavior across scenarios
• **PMs** - Track quality metrics over time, compare experiments, monitor production health
• **SMEs and Annotators** - Label data, review AI outputs, provide human feedback at scale

## Powered by DeepEval

Confident AI's evals are 100% powered by DeepEval, one of the most widely adopted LLM evaluation frameworks with over 13k GitHub stars, 3 million monthly downloads, and 20 million daily evaluations. DeepEval is used by companies such as OpenAI, Google, and Microsoft.

## Supported Use Cases

All types of LLM use cases are supported, including summarization, Text-SQL, customer support chatbots, internal RAG QAs, conversational agents, and more. These can be any architecture - RAG pipelines, agentic workflows, conversational chatbots, or combinations like RAG chatbots and agentic RAG systems.

## Enterprise Ready

Confident AI offers SSO, team-based data segregation, customizable user roles and permissions, and self-hosted deployment options. Deploy in your own cloud environment via Docker with integration to your identity providers (Azure AD, Okta, Ping). HIPAA compliant with BAA available on Premium plans and above.

## AWS Deployment

Self-host Confident AI in your AWS environment via Docker for full control over your data and infrastructure. Setup typically takes 1-2 weeks with support from the Confident AI team.