Confident AI

Confident AI is an AI quality and LLMOps platform designed for engineering, product, QA, and AI teams building production generative AI applications. It combines LLM evaluation, experimentation, observability, production monitoring, dataset management, and security testing in one environment. Teams can test AI systems before deployment and then continuously evaluate their behavior after they reach production.

A major part of the ecosystem is DeepEval, Confident AI's open-source LLM evaluation framework. DeepEval provides 50+ evaluation metrics covering areas such as answer relevancy, faithfulness, hallucination, task completion, tool correctness, conversational quality, safety, RAG performance, and multimodal systems. Developers can also create custom metrics and use different LLM providers as judges rather than being locked into one model provider.

Confident AI extends these evaluations into collaborative testing and experimentation. Teams can compare prompts, models, parameters, and application versions; build evaluation datasets; run regression tests; and integrate evaluations into CI/CD pipelines. Evaluation checks can even be configured as required checks so that quality regressions prevent problematic changes from being merged or deployed.

For production applications, Confident AI provides eval-first observability. Developers can trace AI executions through its SDK, OpenTelemetry, and integrations with frameworks such as LangChain and LangGraph. Traces can automatically receive quality scores, while thresholds and alerts help teams detect prompt drift, hallucinations, performance regressions, and other quality problems. Production traces can also be curated into new evaluation datasets, creating a feedback loop between real-world usage and future testing.

The platform additionally supports AI red teaming and security testing, enabling teams to identify vulnerabilities such as prompt injection, PII leakage, bias, misinformation, and excessive agent permissions. This makes Confident AI relevant not only for traditional LLM applications but also for increasingly complex AI agents and tool-using systems.

Confident AI offers Free, Starter, Team, and Enterprise tiers, while DeepEval itself remains free and open source under the Apache 2.0 license. This combination makes the ecosystem suitable both for individual developers who want local AI testing and organizations that need collaborative evaluation, observability, governance, and production monitoring.