Keymakr Launches Its SaaS Platform Keylabs, Helping Companies Scale Video Annotation Automatically

Keymakr, a data-annotation service provider delivering high-quality datasets to AI innovators, announces the launch of its SaaS platform, Keylabs. Through Keylabs, Keymakr empowers companies of all sizes, ranging from Zeekit, acquired by Walmart, to smaller companies, to leverage its data annotation tools in-house.

Around 80 percent of the work that goes toward developing AI capabilities lies in collecting and preparing data, a crucial piece in the creation of an ML project. Yet many companies fail to scale and process the immense amount of data needed. Without proper data inputs, major roadblocks can be caused down the road and even result in project failure, leading many companies to leverage outside data annotation tools. But many of these data annotation tools struggle to provide quality results without glitches. Companies struggle to trust data annotation tools that provide poor user interfaces and no QA to ensure accurate results.

Now all companies, regardless of whether they have data-annotation teams, can leverage Keymakr's uniquely effective annotation capabilities through Keylabs, its purpose-built SaaS platform. Keylabs's easy-to-use interface improves the speed of annotation and data sets while ensuring accuracy through its QA abilities.

Keymakr's video annotation supports object tracking and provides one of the most accurate results in the industry for companies in various industries, such as agriculture, waste management, and automotive. The company also works with retail companies, which deal with data that comes from mobile devices, in-store cameras, logistics, and warehouse cameras. Keymakr follows strict data standards and is compliant with the European Union's GDPR (General Data Protection Regulation).

"Data annotation is rapidly expanding, but to make the most of it we have to do it properly," says Arie Zilberman, CEO and founder of Keymakr. "As machine learning becomes increasingly important for virtually every industry, we aim to arm companies with the tools they need to scale data annotation and build their models efficiently and precisely."

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Written by Jessel Thomas