Confident AI
An open-source platform to evaluate, A/B test, and classify LLM outputs, helping developers optimize model accuracy and reliability.
LLM EvaluationA/B TestingOutput ClassificationOpen Source AIModel TestingPrompt Engineering
Confident AI Introduction
Confident AI is an open-source evaluation framework designed to bring rigor to LLM application development. It allows AI engineers to systematically test and compare model outputs using customizable metrics, A/B testing, and automated classification. By integrating these evaluations into the development and deployment pipeline, teams can catch regressions, prevent prompt drift, and ensure their LLM features behave as expected in production. It’s a vital tool for startups and enterprises alike that are serious about shipping reliable AI products.
Key Features
- Set up evaluation metrics for accuracy, relevance, and safety of LLM outputs
- Run A/B tests between different prompts, models, or configurations
- Classify and score outputs automatically to filter low-quality responses
- Generate detailed reports to compare model performance over time
- Self-host or use the cloud version with integration into CI/CD pipelines
