Deepchecks offers LLM Evaluation, a comprehensive solution to evaluate the quality and compliance of LLM apps. With automated evaluation processes, Deepchecks helps detect and mitigate issues such as incorrect answers, bias, hallucinations, and harmful content. Join thousands of practitioners in the LLMOps.Space community. Learn more
Release high-quality LLM apps quickly without compromising on testing. Never be held back by the
complex and subjective nature of LLM interactions.
Evaluation is Complex
Generative AI produces subjective results. Knowing whether a generated text is good usually requires
manual labor by a subject matter expert.
Evaluation is Complex
A small change in the answer might change the meaning of the answer completely.
Evaluate Quality & Compliance
Evaluate quality & compliance
If you’re working on an LLM app, you probably
know that you can’t release it without addressing
countless constraints and edge-cases.
Hallucinations, incorrect answers, bias, deviation
from policy, harmful content and more need to be
detected, explored and mitigated before and
after your app is live.
Deepchecks does it systematically.
Golden Set
A proper Golden Set (The equivalent of a test set for GenAI)
will have at least a hundred examples. Manual annotations
typically take 2-5 minutes per sample, and require waiting,
reviewing, correcting and sometimes hiring.
Good luck with doing this for every experiment or version
candidate!
Deepchecks’ solution enables you to automate the
evaluation process, getting “estimated annotations” that
you only override when you have to.
Open Core Product
DEEPCHECKS LLM EVALUATION IS BASED ON THE LEADING ML OPEN SOURCE TESTING PACKAGE
Used by 1000+ companies, integrated into 300+ open source projects, the core behind our LLM
product is widely tested and robust.
Open Core Product
Open Source ML Testing
Deepchecks Open Source is a Python-based
solution for comprehensively validating your
machine learning models and data with minimal
effort, in both the research and the production
phases.
Open Source ML Testing
ML Monitoring
ML Monitoring
Model performance is a critical component of a
healthy application. To maximize your business
performance, ML and IT teams need to
continuously know the status of their model.
Deepchecks Monitoring makes sure that your
models and data are validated continuously.
LLMOps.Space
Deepchecks is a founding member of LLMOps.Space, a global community for LLM
practitioners. The community focuses on LLMOps-related content, discussions, and
events. Join thousands of practitioners on our Discord.