The best part of Cleanlab is it's AI models which optimizes any pretrained modules with great level of efficiency. Another best part is it's documentation, Any type of users can use Cleanlab by reading it's documentation. And TLM module is best, it optimizes any LLM. It's API feature helps the integration part much easier. Review collected by and hosted on G2.com.
As of now I find it a bit hard to dislike such great module. But still talking about it's dislike : It is expensive and some small startups may not afford it. Also, TLM doesn't do great with unstructured data. Review collected by and hosted on G2.com.
Accurate error detection. The ability to automatically spot mislabeled and low-confidence examples has saved me countless hours of manual review.
Seamless pandas integration. Working directly on DataFrames makes it trivial to plug Cleanlab into existing preprocessing pipelines.
Clear, example-driven docs. The step-by-step tutorials helped me get up and running in under an hour. Review collected by and hosted on G2.com.
Initial setup complexity. Installing all dependencies (and configuring environments) can feel a bit involved if you’re just experimenting.
Performance on very large datasets. Label-error detection can be slow without additional tuning or sampling. Review collected by and hosted on G2.com.
The time we spent in dataset to significanty decrese after using cleanlab. i would say its save lots of time. Review collected by and hosted on G2.com.
sometime it getting slow on large dataset but we have not so frequnt those dataset but yes there is need to improvment. Review collected by and hosted on G2.com.
Easy to use. No much hardware setup is required and the way it helps in refining data & on the e-commerce side is wonderful. Review collected by and hosted on G2.com.
Nothing as such I can think of. need to look more into the product before making any statement. Review collected by and hosted on G2.com.
The AI insights which are there which helps the person do the work in less time. Review collected by and hosted on G2.com.
The delay time is quite high sometimes it takes bit more time than usual Review collected by and hosted on G2.com.
Cleanlab Studio’s big advantage lies in automating the finding of mislabeled data, a game-changer for our AI projects. It boasts an easy-to-use interface and strong algorithms that significantly reduce data cleaning time, thereby allowing our team to engage more on model development. What’s more, this has made it possible to improve workflows through seamless integration with existing data pipelines thus making maintenance of high-quality datasets easier. Review collected by and hosted on G2.com.
The main limitation is that there are no advanced customization options available for the purpose of cleaning up the data. In some cases where more detailed control would have been useful, although automated features can be very effective. Also, setting up initially may be somewhat complicated and requires some familiarization time with all these functionalities. Review collected by and hosted on G2.com.
Automated Data Cleaning
Seamless Integration
Robust Error Detection
Improves Model Accuracy
Support Multiple Data Types Review collected by and hosted on G2.com.
Computational Overhead
Steep Learning Curve
Dependence on Model Predictions
Not Fully Automated
Limited GUI Support Review collected by and hosted on G2.com.
lot of functionalities to play around with . That helps massively as we crunch data sets.very helpful community and support model Review collected by and hosted on G2.com.
difficult to use but very handy once you get hang of it. Docuemntation is improving. The community is growing . Review collected by and hosted on G2.com.
I like it's ability to clean data automatically. Review collected by and hosted on G2.com.
It is unnecessary for a small business like ourselves. We do not need to outsource. This is the kind of thing that large companies need to quickly examine unruly amounts of data. Review collected by and hosted on G2.com.