Combine powerful automation tools with state of the art pre-labeling techniques to speed up labeling by 65% without sacrificing quality. Track, measure, and improve your pre-labeling efficiency with a single metric and focus human labeling efforts on review and edge-cases.Learn more
Create dynamic workflows based on attributes like annotation type or labeler to reduce cost and increase labeling and review throughput, quality, and efficiency. Generate high-quality labels with less team time.Learn more
Our world-class labeling partners have subject matter expertise ranging from agriculture and fashion to medical and life sciences and are proficient in over 20 languages. Regardless of your use case, we’re here to help, and we have experienced teams available on-demand.Learn more
Experience the next level of productivity and cost gains by unifying all data labeling projects within a single platform. Plug-in internal workforce, bring your external workforce, use Labelbox Boost, or use all of them simultaneously to create the highest quality data.
Operationalize large-scale labeling with comprehensive and granular analytics covering throughput, efficiency, and quality across every workforce on the platform. Use data-driven insights to manage human labeling cost and quality.Learn more
Powerful communication and collaboration tools bring your teams, from data engineers to external labeling workforces, closer together than ever. Get live project status updates and collaborate on labeling issues in real time all in a single platform.
Labelbox natively supports image, video, text, PDF document, tiled geospatial, medical imagery, and audio data. Whatever your task, Labelbox has purpose-built tools to support you.
How Blue River Technology's data engine automates data curation and labeling from 1B+ assets
Blue River Technology needed to rapidly scale and optimize their computer vision model development pipeline and decrease their iteration cycles — which often took several weeks — to hours in order to deliver the best AI-powered products. Two of the primary causes of delay in their processes were data management and infrastructure being created and maintained by ML engineers and an arduous data curation process that took longer and became more painful as the amount of data increased exponentially.
The team built a unified machine learning and data engine that leverages embedded integrations with best-in-class data storage and management, data curation, and labeling solutions. The platform also includes multiple robust and innovative applications designed to increase efficiencies and reduce ML engineering workloads.
With the new data engine, Blue River Technology’s ML teams can now spend more of their time focusing on training, monitoring, and maintaining their computer vision models. Their data scientists can pull updated, refined, relevant datasets for every use case and model within minutes via Labelbox Catalog.
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