What is Confident AI?
Confident AI is your go-to platform for evaluating, benchmarking, and improving the performance of LLM (Large Language Model) applications. With best-in-class metrics and guardrails, it helps you safeguard your AI systems while optimizing prompts and models. Whether you're a small startup or a large enterprise, Confident AI ensures your LLM applications are top-notch.
What are the features of Confident AI?
- LLM Evaluation: Benchmark and test your LLM systems to catch regressions and optimize performance.
- LLM Observability: Monitor, trace, and A/B test your LLM applications in real-time.
- Dataset Curation: Annotate and update datasets with the latest production data.
- Custom Metrics: Tailor evaluation metrics to align with your specific use case.
- Pytest Integration: Unit test LLM systems in CI/CD pipelines without changing your workflow.
What are the use cases of Confident AI?
- Optimizing LLM Prompts: Experiment with different prompts to find the most effective ones.
- Cost Reduction: Cut LLM costs by fine-tuning models and improving efficiency.
- Performance Monitoring: Track real-time performance and detect any drifts.
- Collaborative Workflows: Centralize dataset curation and evaluation for teams.
How to use Confident AI?
- Install the DeepEval package:
pip install -U deepeval. - Pull your dataset:
dataset.pull(alias="QA Dataset"). - Run evaluations:
dataset.evaluate(metrics=[AnswerRelevancy()]). - Monitor LLM outputs: Use
deepeval.monitor()to track inputs and responses.
