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The LLM Evaluation Platform.
Companies of all sizes use Confident AI to justify why their LLM applications - RAG, Agents, or Chatbots, deserves to be in production.
TRUSTED BY COMPANIES AROUND THE WORLD
Automatically Catch Regressions in LLM Systems.
An all-in-one LLM evaluation platform to easily evaluate, compare, and share test results to identify LLM regressions.
LLM Evaluation Metrics for any use case.
Evaluate on any criteria using research-backed custom metrics, proven to be as accurate and reliable as human evaluation.
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4.28m
Evaluations completed
Metrics are battle-tested with over 4 million evaluations ran.
12+
Metrics available
Metrics to cover use cases such as RAG, agents, or LLM chatbots.
Generate evaluation datasets on the cloud.
Generate, upload, edit, and delete test cases to manage evaluation datasets on one centralized platform.
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100k+
Test Cases Generated
Generate test cases to evaluate LLM systems at scale.
31+
Hours Saved Per Week
Reduce friction between data annotators and engineers.
Discovery optimal LLMs for your use case.
Discovery which combination of hyperparameters such as LLMs and prompt templates works best for your LLM app.
2.4x
Less time to production
No more time wasted on finding breaking changes.
1.42m
Evaluations completed
Users evaluate by writing and executing test cases in python.
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from deepeval import confident_evaluate
test_case = LLMTestCase(input="...", actual_output="...")
confident_evaluate(experiment_name="RAG Test", test_cases=[test_case])
> pip install -U deepeval
> deepeval test run test_llm.py
✓ Test Run Completed.
✓ 1/1 test case(s) passing.
Open-source and simiple to integrate.
Run evaluations on the cloud through simple APIs through DeepEval, the LLM evaluation framework.
2.4x
Less time to production
No more time wasted on fixing breaking changes.
12+
Metrics available
Metrics to cover use cases such as RAG, agents, or LLM chatbots.
1.42m
Evaluations completed
Users evaluate by writing and executing test cases in python.
100%
Sleep better
Customers sleep better knowing their LLM is behaving as expected
Judge your LLM application on one, centralized platform.
Deploy LLM solutions with confidence, ensuring substantial benefits and address any weaknesses in your LLM implementation.
Define ground truths to ensure your LLM is behaving as expected
Supply ground truths as benchmarks to evaluate your LLM outputs. Evaluate performance against expected outputs to pinpoint areas for iterations.
Advanced diff tracking to iterate towards the optimal LLM stack
From altering prompt templates to selecting the right knowledge bases – we guide you towards the optimal configurations for your specific use case.
LLM observability and monitoring to identify areas of focus
Utilize out-of-the-box observability to identify and evaluate use cases that bring the most ROI for your enterprise.
Powerful features to productionize LLMs with confidence.
A/B testing
Compare and choose the best LLM workflow to maximize your enterprise ROI.
Evaluation
Quantify and benchmark your LLM outputs against expected ground truths.
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Output classification
Discover recurring queries and responses to optimize for specific use cases.
Reporting dashboard
Utilize report insights to trim LLM costs and latency over time.
Dataset generation
Automatically generate expected queries and responses for evaluation.
Detailed monitoring
Identify bottlenecks in your LLM workflows for targeted iteration and improvement.
Book a demo today.
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1. Create account
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2. Integrate with your tools
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3. Close more sales
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Rebeca Miller
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The future of evaluation depends on you.
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Sales teams
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Marketing teams
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Support team
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