Paytm (One97 Communications Ltd) has announced a partnership with US-based AI hardware company Groq, aiming to use Groq’s purpose-built Language Processing Units (LPUs) to power real-time artificial intelligence (AI) across its payments and financial services platforms.
The collaboration, announced on November 5, 2025, will see Paytm deploy GroqCloud, which runs on LPUs designed to perform AI inference faster and at lower cost compared to traditional GPU-based systems. According to both companies, this will help Paytm improve speed, efficiency, and scalability of AI-driven functions across its ecosystem.
Paytm already uses AI in several mission-critical areas, from fraud detection and risk modelling to customer onboarding and personalization. The company said the tie-up with Groq will deepen its technological capabilities by enabling real-time AI inference at scale, a step towards what it calls the “next phase of intelligent and data-driven growth.”
Commenting on the development, Narendra Singh Yadav, Chief Business Officer at Paytm, said the partnership “strengthens our technology foundation by enabling real-time AI inference at scale.” From Groq’s side, Scott Albin, General Manager (APAC), said the collaboration reflects Groq’s broader mission “to deliver broad compute capacity” and make AI “useful and accessible” to enterprises at scale.
From a business perspective, the partnership could enhance Paytm’s operational intelligence, improving the speed of transaction processing, accuracy of risk assessment, and effectiveness of fraud prevention systems. It may also enhance customer engagement by allowing faster, more contextual responses across Paytm’s app and financial products.
For Groq, the Paytm alliance represents a significant commercial and visibility milestone in India, positioning the firm as an infrastructure provider for large-scale financial applications. The collaboration extends to Paytm’s associate entities, suggesting that the deployment may cover the company’s broader ecosystem beyond just payments.
However, the article notes that no financial details of the deal were disclosed. The companies have not specified the timeline for full rollout or the exact operational scale expected once integration is complete. Likewise, there are no disclosed metrics yet for the performance gains or cost savings expected from shifting to LPUs.
Even so, the announcement underlines a growing industry trend, financial-technology firms increasingly partnering with specialised AI hardware providers to boost compute efficiency, manage costs, and build proprietary capabilities in the face of growing data loads.