TDCX Forms Strategic Partnership with SUPA to Address Data Labelling Challenges in AI Implementation

In today’s rapidly evolving digital landscape, the integration of artificial intelligence (AI) technologies has become increasingly crucial for businesses looking to stay competitive and drive innovation. However, one of the key challenges hindering the successful implementation of AI is the accurate labelling of raw data to make it comprehensible for machine learning algorithms.

Recognizing this challenge, TDCX has formed a strategic partnership with SUPA, a company specializing in generative AI-powered data labelling. This collaboration aims to provide businesses with an integrated solution that combines cutting-edge technology and human expertise to deliver high-quality data outputs, ultimately enabling more efficient training of AI models.

According to a McKinsey report, 72% of leading organizations identify data handling as a major obstacle in AI scaling, with 81% finding the task of training AI with data more complex than expected. This partnership between TDCX and SUPA addresses these challenges by leveraging SUPA’s capabilities for managing extensive datasets and employing human annotators to reduce data processing times significantly.

Ms Lianne Dehaye, Senior Director of TDCX AI, emphasized the importance of accurate data in the successful deployment of generative AI, stating that without structured and reliable data, businesses are not ready to leverage AI effectively. She also highlighted the need for quality data in customer experience applications, where human intelligence plays a crucial role in ensuring data accuracy and sensitivity to cultural nuances.

Mark Koh, CEO and co-founder of SUPA, highlighted the accuracy of their platform, which processes large training datasets with up to 98% accuracy through a multi-stage human-in-the-loop approach. He emphasized the platform’s ability to curate and process data accurately, empowering annotators to minimize errors and routing issues.

The collaboration between TDCX and SUPA is designed to cater to various industries, including consumer retail, transport, agriculture, manufacturing, and healthcare, supporting diverse data types such as visual data, multilingual texts, and audio data. Both companies assure that data handled within this collaboration will be managed securely, with clients retaining ownership within their own cloud storage.

As part of the collaboration launch, TDCX and SUPA are offering a complimentary diagnostic session to help companies identify opportunities or gaps in their data labelling needs, facilitating a smoother adoption of AI technology. This partnership is positioned to provide a comprehensive solution to the data labelling challenges faced by enterprises, enabling more efficient integration of AI technologies in business operations.

Overall, the collaboration between TDCX and SUPA represents a significant step towards overcoming the obstacles in AI implementation, offering businesses a streamlined and effective solution for data labelling and training AI models. With the combined expertise of both companies, businesses can harness the power of AI more efficiently and drive growth and innovation in their operations.