Scale GenAI Platform has made it much more manageable for us to prepare and label training data for our customer support assistant. It gives us access to structured data pipelines and human-in-the-loop annotation without having to build that infrastructure ourselves. The ability to combine automated processing with human review for edge cases has noticeably improved the quality of our training data versus relying only on automated labeling. Integration into our existing model-training workflow was smooth, and the platform’s tools for handling large volumes of data have continued to scale well as our dataset needs have grown. Review collected by and hosted on G2.com.

Pricing can add up quickly on larger data-labeling projects, especially when human review is needed for more nuanced or ambiguous cases. Setting up custom labeling workflows for our specific domain—like logistics and trip-related terminology—took a fair amount of time to configure correctly. Turnaround times for human-reviewed batches can also vary, which occasionally slowed our iteration when we needed fast feedback on labeling quality. The documentation covers common use cases well, but more advanced customization still required additional support engagement. Review collected by and hosted on G2.com.