Supahands Announces Launch of The Supahands Opus Infrastructure to Support Global Growth and Competitive Advantage

Kuala Lumpur, Malaysia – 12 May 2020:  Supahands, the leading global data labeling partner for quality Machine Learning and Artificial Intelligence training data sets, today announced the launch of its Opus Infrastructure (OI). 

The OI offers a fully-managed customer experience for a wide variety of data labeling needs, such as image annotation, sentiment tagging and data transcription. Featuring Supahands’ sophisticated proprietary technology, the OI enables organizations to boost operational agility and accelerate competitive advantages by engaging an end-to-end managed service that produces quality training data for Machine Learning and Artificial Intelligence at scale, with customisable technology and project-specific workflows.

“We are committed to helping our customers stay at the forefront of their industry by understanding the need and importance of high-quality training data, and we pride ourselves in ensuring that every project we deliver is completed at high quality and high accuracy – with minimal disruption to the customers.” said Mark Koh, CEO and co-founder at Supahands. 

“The experience of working with us is just as important as the quality of work that we deliver and clients need to know that they have a partner that they can trust to be fully transparent and accountable for their data labeling needs. OI was built to consolidate our strengths, from our personalized project guidelines, ultra-flexible platform customizations to efficient communication plans to adapt to their specific requirements. We are providing our clients a stress and hassle-free process in attaining high-quality training data.”

With demand for Artificial Intelligence solutions steadily on the rise, Supahands’ OI also supports the ever-shifting technological automation landscape by providing an agile and flexible solution for data labeling workflows.  

“Ultimately, how efficient and flexible a data labeling process is, contributes to the end goal of achieving quality in training data, which plays an important part in the accuracy of AI and Machine Learning models.”

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