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TDCX acquires Malaysian firm Supa to boost AI platform Chemin
TDCX Group has acquired SUPA, a data labeling and annotation platform.
This acquisition will integrate SUPA into Chemin, TDCX’s AI enablement subsidiary, to address the growing demand for advanced data services.
SUPA brings expertise in data interpretation, prompt engineering, and synthetic data validation for complex AI systems.
TDCX CEO Laurent Junique said the deal strengthens their curated data offerings, while SUPA CEO Mark Koh highlighted its impact on AI decision-making.
Chemin, launched in 2025, provides services like data annotation and model evaluation, now expanded with SUPA’s tools.
The move positions TDCX to grow in the AI enablement market as demand for AI infrastructure accelerates.
🔗 Source: TDCX
🧠 Food for thought
1️⃣ Consolidation in CX industry shifts toward AI capability acquisition
TDCX’s acquisition of SUPA reflects a strategic consolidation trend in the customer experience industry, where companies are prioritizing AI capabilities over traditional operational scale.
This contrasts with previous major CX acquisitions like Concentrix’s $2.43 billion purchase of Convergys (2018) and Telus International’s €915 million acquisition of Competence Call Center (2019), which primarily focused on expanding geographic footprint and operational capacity12.
Today’s acquisitions increasingly target specialized AI expertise rather than just service delivery capacity. TDCX’s integration of SUPA into Chemin, their AI enablement subsidiary, rather than their core CX operations, illustrates this shift3.
The industry has moved from acquiring market share to focusing on intellectual property and specialized talent, reflecting how AI is transforming the economics and value proposition of customer experience providers.
McKinsey’s research reveals that while 92% of companies plan to increase AI investments, only 1% consider themselves “mature” in AI deployment. This creates strong incentives for established players to acquire rather than build these capabilities4.
2️⃣ Data labeling evolves from basic tagging to specialized knowledge work
The acquisition highlights how data labeling has transformed from a relatively simple task to highly specialized knowledge work requiring advanced expertise and domain-specific training.
