Labelbox is a collaborative training data platform empowering teams to rapidly build artificial intelligence applications.
6 key best practices for AI teams to save time when creating AI data
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.
Optimize the efficiency and quality of your training data with our newest features
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.
How Deque uses data prioritization and model diagnostics to unlock AI breakthroughs in digital accessibility
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.
Increase labeling velocity and optimize workflows with our newest features
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.
Streamlined data management and key editor improvements
We've focused recent product development on streamlining essential data management workflows and are introducing new collaboration tools for labeling operations and labeling teams. We’ve also made some key updates to our Editors that enable more complex ML use cases and improve usability.