Evaluation Infrastructure for LLMs.

Companies of all sizes use Confident AI to justify why their LLM deserves to be in production.

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test_chatbot.py
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from deepeval import assert_test
from deepeval.metrics import HallucinationMetric
from deepeval.test_case import LLMTestCase
 
def test_example();
test_case = LLMTestCase(input="...", actual_output="...")
metric = HallucinationMetric(minimum_score=0.7)
assert_test(test_case, [metric])
> pip install -U deepeval
> deepeval test run test_chatbot.py
Test Run Completed.
1/1 test case(s) passing.

Open-source and simple to use.

We offer a generous free tier and anyone can get started in under 10 lines of code.

2.4x

Less time to production

No more time wasted on fixing breaking changes.

12+

Metrics available

We offer plenty of open-source metrics for you to plug and use.

31k

Evaluations completed

Users evaluate by writing and executing test cases in python.

100%

Sleep better at night

Our users 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.

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.

Comprehensive analytics 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.

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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.

Output classification

Discover recurring queries and responses to optimize for specific use cases.

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Reporting dashboard

Utilize report insights to trim LLM costs and latency over time.

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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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