Friday, November 22, 2024

Deepen’s AI-Powered Auto-Labeling Technology Significantly Brings Down Labeling Effort

Deepen AI’s proprietary auto-labeling technology helps enterprises automate labeling for up to 80 categories – increasing productivity by 7X while maintaining high levels of accuracy.

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Data labeling is required for a variety of use cases including computer vision. Labeling a large amount of data can be tedious & time-consuming. To help humans minimize the hard work and effort of data labeling from scratch, Deepen AI has developed an automated solution, aiming to reduce most of the manual work.

“Manual labeling becomes unscalable past a certain data volume. The demand for high-quality annotated data is increasing rapidly and with our AI-powered easy to use annotation and review tools, enterprises and individuals can reduce annotation time and effort significantly – while maintaining the highest quality.” – Mohammad Musa, CEO and Founder, Deepen AI

Working closely with enterprises to devise custom plans and models, Deepen AI is able to leverage years of experience to deliver high-quality automation even for challenging tasks.

On top of Deepen‘s auto-labeling solution, Deepen AI’s annotation tool also provides enterprises with features to easily manage, track and increase productivity:

Reporting – To support all business needs to give clients key information with a click of a button.
Task Management – Complete lifecycle of tasks made to support huge annotation teams, with the ability to streamline and automate your dataset workflow experience.
Quality Assurance – Built-in QA flow allows enterprises to easily verify the quality of processed data to maintain quality standards with features like sub-sampling, comments and automatic checker.

Deepen AI is the only safety-first data lifecycle tools and services company focused on machine learning and AI for autonomous systems. With tools and services that are customizable to suit the needs of enterprises as well as start-ups they have happy customers of every size across the globe.

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