Confident AI

Eval-first LLM observability platform that traces, tests, and monitors AI apps in production.

Freemium Coding & Development
Visit Website ↗ by Confident AI

What is Confident AI?

Confident AI is an AI quality platform built by the creators of the open-source DeepEval evaluation framework. It gives engineering, QA, and product teams one shared place to evaluate, observe, and improve LLM applications from prototyping through production. Every LLM call is captured as a trace with full context — inputs, outputs, tool calls, latency, and token cost — and scored with 50+ research-backed metrics. Production failures are automatically curated into evaluation datasets and CI/CD regression gates, while non-engineers can run prompt and model experiments directly.

Key features

  • OpenTelemetry-native LLM tracing across 20+ frameworks and providers
  • 50+ research-backed evaluation metrics for quality, safety, and hallucinations
  • Online evals and alerting on live production traces
  • Automatic evaluation dataset curation from production traces
  • CI/CD regression gates via the DeepEval open-source framework
  • Annotation workflows with human review queues
  • Multi-turn chat simulations for chatbot testing
  • Red teaming and AI risk assessment workflows
  • Self-hosting on Enterprise plan

Pros

  • Combines tracing and evaluation in one workflow instead of separate tools
  • Built by the team behind DeepEval, one of the most adopted LLM eval frameworks
  • SOC 2 Type II compliant with VPC/on-prem deployment option
  • Free tier available for getting started

Cons

  • Self-hosting is limited to the Enterprise plan
  • Pricing for paid tiers is not fully public
  • Deepest value is for teams shipping AI products, less so for solo prototypers

Confident AI at a glance

PricingFreemium
CategoryCoding & Development
Platformsweb, api
CompanyConfident AI
Official websitewww.confident-ai.com
llm-evaluationllm-observabilityai-testingdeepevalred-teamingproduction-monitoring

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The right coding tool depends on where you write code and how much of your codebase it can understand. IDE integration is the first filter — a tool that lives in your editor, sees your project files and respects your stack will help far more than a general chatbot you paste snippets into. Look for accurate completions, clear explanations of suggested changes, and strong refactoring and debugging support for your main languages. Privacy deserves real attention: check whether your code is used for training, and whether a self-hosted or enterprise option exists for sensitive projects. Price against the hours it actually saves — most developers feel the difference within the first week of real use.

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Confident AI FAQs

What is Confident AI?

Confident AI is an AI quality platform built by the creators of the open-source DeepEval evaluation framework. It gives engineering, QA, and product teams one shared place to evaluate, observe, and improve LLM applications from prototyping through production. Every LLM call is captured as a trace with full context — inputs, outputs, tool calls, latency, and token cost — and scored with 50+ research-backed metrics. Production failures are automatically curated into evaluation datasets and CI/CD regression gates, while non-engineers can run prompt and model experiments directly.

What are the main features of Confident AI?

Confident AI offers OpenTelemetry-native LLM tracing across 20+ frameworks and providers, 50+ research-backed evaluation metrics for quality, safety, and hallucinations, Online evals and alerting on live production traces, Automatic evaluation dataset curation from production traces, CI/CD regression gates via the DeepEval open-source framework, Annotation workflows with human review queues, Multi-turn chat simulations for chatbot testing, Red teaming and AI risk assessment workflows and Self-hosting on Enterprise plan.

How much does Confident AI cost?

Confident AI follows a freemium model: a free tier is available, and paid plans unlock higher limits and advanced features. Check its official website for current plan prices.

What are the pros and cons of Confident AI?

Strengths of Confident AI include Combines tracing and evaluation in one workflow instead of separate tools; Built by the team behind DeepEval, one of the most adopted LLM eval frameworks; SOC 2 Type II compliant with VPC/on-prem deployment option. On the downside, Self-hosting is limited to the Enterprise plan; Pricing for paid tiers is not fully public; Deepest value is for teams shipping AI products, less so for solo prototypers.