Confident AI, built by the creators of DeepEval, is an LLM evaluation platform designed for engineering teams to benchmark, safeguard, and improve LLM applications. It offers tools for dataset curation, metric alignment, and automated LLM testing with tracing.
Key Features:
- LLM Evaluation: Benchmark LLM systems to optimize prompts and models, and catch regressions using metrics powered by DeepEval.
- LLM Observability: Monitor, trace, A/B test, and gain real-time production performance insights with best-in-class LLM evaluations.
- End-to-End Evaluation: Measure the performance of prompts and models using Confident AI's evaluation suite.
- Regression Testing: Mitigate LLM regressions by running unit tests in CI/CD pipelines.
- Component-Level Evaluation: Evaluate individual components with tailored metrics to pinpoint weaknesses in your LLM pipeline.
- DeepEval Integration: Easily integrate evaluations using DeepEval, with intuitive product analytic dashboards.
Use Cases:
- AI Moat Building: Curate datasets, align metrics, and automate LLM testing with tracing.
- Regression Mitigation: Safeguard AI systems to reduce time spent fixing breaking changes.
- Cost Reduction: Cut inference costs by optimizing LLM performance.
- Stakeholder Confidence: Demonstrate consistent AI performance improvements.
