We’ve focused recent product development on end-to-end workflow to help teams iterate and ship models faster than ever. Curate and prepare training datasets, have greater visibility into the processing status and searchability of your data rows, SDK updates, and more.
Wading through a vast amount of unstructured data to accurately annotate assets requires a tremendous amount of patience, organization, and time. Learn six key time-saving practices for ML teams to implement when handling AI data.
We’ve focused recent product development to help users better optimize the throughput, efficiency, and quality of training data production. You can now more powerfully search for data rows within a project, visualize ground truth and predictions in Catalog, and more.
Deque has developed a sophisticated data engine that’s capable of prioritizing the most performant classes of data, discovering model errors quickly, and fueling their iterations with high-quality data.
We’ve continued to focus product development to help teams increase labeling velocity and optimize their data management workflows. We’re also excited to announce key improvements to our editors to better support text and documents.
