TDCX has formed a strategic partnership with SUPA, a company specialising in generative artificial intelligence (AI)-powered data labelling, to address a significant challenge in AI implementation - the labelling of raw data to make it comprehensible for machine learning algorithms.
Handling data remains one of the primary obstacles hindering AI scaling for enterprises, with 72% of leading organisations identifying it as a major challenge, according to a McKinsey report. Moreover, 81% of these organisations have found the task of training AI with data more complex than initially expected, as noted by TechHQ.
This collaboration aims to provide businesses with an integrated solution that combines cutting-edge technology and human expertise to deliver high-quality data outputs. Leveraging SUPA's capabilities for managing extensive datasets and employing human annotators, the partnership is expected to reduce data processing times significantly. This hybrid approach is designed to enable businesses to train their AI models more efficiently, thereby enhancing the overall value generated from AI applications.
Ms Lianne Dehaye, Senior Director of TDCX AI, commented on the importance of accurate data in the successful deployment of generative AI.
"Without accurate, structured, and reliable data, your business simply isn't ready to leverage generative AI. With the strong interest in generative AI, many companies find themselves in a rush to benefit from it. However, the truth is, many companies either do not take the critical first step of data labeling or underestimate the resources needed to get it done well. This leads to situations where AI projects end up failing and there is little return on that investment," she said.
She further highlighted the need for quality data in customer experience (CX) applications, noting that data must be devoid of bias and sensitive to cultural nuances, areas where human intelligence plays a crucial role. "Our collaboration with SUPA strengthens our offerings and will enable us to help clients integrate AI into their CX strategies more quickly and easily," she added.
Mark Koh, Chief Executive Officer and co-founder of SUPA, emphasised the accuracy of their platform, which processes large training datasets with up to 98% accuracy through a multi-stage human-in-the-loop approach. "Our platform's edge lies in our ability to curate and process large training datasets with up to 98 per cent accuracy for labeled data. Achieved through our multi-stage human-in-the-loop approach, this proactive validation process empowers annotators to act as data model teachers, thus minimizing potential errors or routing issues. We look forward to tapping TDCX's global scale and strong network of clients to help more companies unlock the power of their data and transform their operating models for efficiency and growth," he stated.
SUPA's solution is designed to cater to various industries, including consumer retail, transport (autonomous vehicles), agriculture, manufacturing, and healthcare. It supports diverse data types such as visual data (images and videos), multilingual texts, and audio data, ensuring that clients receive precise and relevant training data tailored to their specific industry needs.
Both companies assure that all data handled within this collaboration will be managed securely, with clients retaining ownership within their own cloud storage.
The companies are also certified for ISO27001, SOC2, and General Data Protection regulations, underscoring their commitment to data security.
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. This initiative aims to facilitate a smoother and more efficient adoption of AI technology across various business sectors.
The partnership between TDCX and SUPA is positioned to provide a comprehensive solution to the data labelling challenges that many enterprises face in their AI journey, thus enabling more efficient and effective integration of AI technologies in business operations.
