Can I do _ _ _ _ with your software?
Start by looking through our . If you don’t find what you’re seeking, do note that: Cleanlab provides significantly more functionality for Enterprise customers than is available in the generally available public version of our software. Learn more in a .
How can I best use your software in my Data / AI projects?
For Enterprises, we offer Proof-of-Value services where our engineers will run the software on your data to show you why thousands of data scientists across all industries use Cleanlab software. Learn more in a . We also offer non-AGPL licenses for the Open-Source packages that come with support from our engineers, as properly using these packages requires ML expertise.
How does Cleanlab Studio compare to existing software and fit into my workflows?
Since Cleanlab Studio is a novel type of Data-Centric AI platform based on years of research from our team, it can be tricky to understand in terms of existing tools (no other tool like this exists). Read that situates Cleanlab Studio in the landscape of existing software tools and Data/AI workflows.
Where can I learn more about the differences between Cleanlab Studio and the Open-Source package?
Read that details the differences.
Do you offer discounts for academic research and small startups?
Absolutely, we enthusiastically support research (and ) and new innovative organizations. Just email:
Can one person really handle: labeling & curating a big dataset + training and deploying a reliable ML model on it?
Absolutely, there have been many stories of a single data scientist or engineer building deployed ML applications from scratch at their company in days. This is possible because Cleanlab Studio automates lots of the work for you, leaving you to only handle the most impactful decisions (and you can do it all without having to write code). Cleanlab Studio offers automated support for: data labeling, data issue detection and correction, ML model training with hyperparameter-tuning and model-selection, and ML model deployment to serve predictions.