G2

Anit S.

Enterprise Architect

Small-Business (50 or fewer emp.)

8/23/2026

"Strong custom text modeling without heavy ML overhead"

4.5/5

What do you like best about Google Cloud AutoML Natural Language?

I appreciate how AutoML Natural Language allowed me to train my own text models for classification and sentiment analysis without having to build a complete machine learning pipeline myself because it is user-friendly and helps identify what data I need to improve. The software's ability to provide a reliable overview of the model's performance and level of each label allows me to see the strengths and weaknesses of my data. I was also able to use this tool within my Google Cloud Platform and only pay for the amount of usage I actually need. Review collected by and hosted on G2.com.

What do you dislike about Google Cloud AutoML Natural Language?

The initial data preparation and annotation could take a long time depending on how similar the categories are and how much work goes into preparing the training set. It would be nice if the onboarding process was a bit more guided with suggestions on what to do with the data set to achieve good results. Review collected by and hosted on G2.com.

What problems is Google Cloud AutoML Natural Language solving and how is that benefiting you?

We used to spend hours doing manual classifications of unstructured text and tinkering with homegrown models, but we can now train models for our own categories and automate much of the classification. The biggest benefit is the reduction in time spent on manual reviews, while the model evaluation tools facilitate iteration without having to start from scratch. The usage-based payment plan also makes smaller jobs more viable, and once the training data is prepared, things move much faster than before. Review collected by and hosted on G2.com.