Confident AI: Observability, Prompts & Evals
Confident AI: Observability, Prompts & Evals
Founded 2024|San Francisco, California, USA|7 employees|Open Source
What is Confident AI?
Confident AI is a Y Combinator-backed AI quality platform that enables engineers, QA teams, and product leaders to build reliable AI systems through comprehensive LLM evaluation and observability capabilities. The platform combines 30+ LLM-as-a-judge metrics for testing and validation with real-time production alerts and tracing capabilities. Teams can perform component-level analysis to evaluate individual pipeline components granularly, integrate regression testing into CI/CD pipelines to prevent LLM performance degradation, and leverage built-in dataset management tools for curation and editing. The platform is built on top of the popular open-source DeepEval framework with 10,000+ GitHub stars and 100,000+ monthly documentation reads. Confident AI offers enterprise-grade features including HIPAA and SOC 2 compliance, multi-data residency in US and EU, RBAC controls, 99.9% uptime SLA, and on-premises deployment options.
Key features
Core capabilities this platform advertises.
- DeepEval open-source evaluation framework
- 14+ evaluation metrics
- Benchmarking suite
- Pytest integration
- Conversational evaluation support
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- Built on popular open-source DeepEval framework with strong community (10,000+ GitHub stars)
- Comprehensive evaluation with 30+ LLM-as-a-judge metrics out of the box
- Y Combinator-backed with proven enterprise compliance (HIPAA, SOC 2)
- Affordable pricing starting at $29.99/user/month with free tier available
- Active community with 2,500+ Discord members and strong documentation
Cons
- Small team of 7 employees may limit support capacity
- Recently founded in 2024, platform may lack maturity of older competitors
- Per-user pricing model can become expensive for larger teams
Common use cases
Developers who want to add automated LLM evaluation testing to their CI/CD pipeline
- Unit testing LLM applications
- Automated evaluation in CI/CD pipelines
- Benchmarking across model versions
- RAG evaluation with custom metrics
- Regression testing for prompts
Run Confident AI in production with Respan
10K Free traces/mo
500+ Models
5 min Setup
Respans lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.
Best Confident AI alternatives & competitors
Top companies in Observability, Prompts & Evals you can use instead of Confident AI.
- Respans - LLM tracing, evals, and gateway
- LangSmith - Trace visualization for LLM chains
- MLflow - OpenTelemetry-native tracing
- Weights & Biases - ML experiment tracking
- Langfuse - Open-source LLM observability
- Arize AI - ML observability with LLM support
- Datadog LLM - LLM monitoring within Datadog platform
- Helicone -
- Traceloop - OpenTelemetry
- Braintrust - Real-time LLM logging and tracing
Compare Confident AI
Side-by-side comparisons with other tools in this category.
- Confident AI vs Respan
- Confident AI vs LangSmith
- Confident AI vs MLflow
- Confident AI vs Weights & Biases
- Confident AI vs Langfuse
Best integrations for Confident AI
Companies from adjacent layers in the AI stack that work well with Confident AI.
- Claude Code - Coding Agents
- Cursor - Coding Agents
- Anthropic MCP - MCP Tooling
- LangChain - Agent Frameworks
- OpenClaw - Agent Frameworks
- AutoGPT - Agent Frameworks
- OpenAI Codex - Coding Agents
- Anthropic Computer Use - Browser Agents
- CodeRabbit - Code Review
- GitHub Copilot - Coding Agents
- Replit - No-Code AI Builders
- Zapier - Workflow Automation