Can Razorpay Turn ChatGPT Into India’s Next Commerce Channel?

ChatGPT is beginning to emerge as more than a search assistant for ecommerce. For a growing number of brands and marketplaces, it is also becoming a new channel for product discovery and, increasingly, shopping.

Nykaa offered one of the clearest signals of that shift in its recent Q1 FY27 management commentary.

The beauty retailer said it has become the top beauty brand on ChatGPT and Gemini through what it calls “Answer Engine Optimization” (AEO), and indicated that AI answer engines are emerging as a customer acquisition channel alongside Google Search. 

It also announced plans to bring Nykaa Beauty and Nykaa Fashion shopping experiences into ChatGPT as part of a broader OpenAI partnership.

If AI assistants become another place where consumers discover products, merchants will need more than visibility, they will also need the ability to complete transactions inside those conversations. That is the opportunity Razorpay is betting on.

Months before AI commerce entered mainstream investor conversations, the payments company began working with OpenAI and NPCI on infrastructure that enables merchants to build ChatGPT-native storefronts and complete purchases within the chat interface. 

According to CEO Harshil Mathur, Razorpay is currently working with around 50 brands and several ecommerce marketplaces experimenting with agentic commerce, with skincare brand Innovist among the first to go live on its ChatGPT commerce stack for select users.

The experience will be enabled on UPI Reserve Pay, which allows users to block a specific amount of funds for future debits to designated merchants, and UPI Circle, a solution that delegates UPI authentication, enabling payments to be completed directly within ChatGPT without switching to external apps or websites.

Razorpay sees its role extend beyond payments to helping merchants integrate product catalogues and storefronts into AI platforms, while using NPCI’s UPI Circle and UPI Reserve Pay to enable native checkout. 

Rival Cashfree, meanwhile, has launched “Cashfree Here”, a payments extension for AI applications that enables in-chat transactions on platforms such as ChatGPT and Claude, highlighting how payment companies are taking different approaches to AI-native commerce.

Mathur, while disclosing the AI roadmap in an earlier interview with us, had stated that the real fight in Indian commerce over the next few years won’t be over who owns the checkout button, but over who owns the conversation that precedes it — and that whoever wins that layer effectively controls the transaction.

Besides ChatGPT, Razorpay is also looking at integrations with other AI models like Anthropic’s Claude and Google’s Gemini for agentic payments products.

From AI Agents To ChatGPT Storefronts

Razorpay has framed the shift as setting up shop inside ChatGPT or ChatGPT Storefronts that would otherwise require a merchant to host their own MCP server and build a new checkout flow from scratch — commonly an eight-to-ten-week engineering effort.

The pitch is that startup collapses this timeframe into something closer to half an hour for a Shopify merchant, auto-syncing the catalogue and handling the submission process to OpenAI on the brand’s behalf.

Cashfree, on the other hand, has got started with agentic payments products, but that will still require the merchants to build their own AI agents which could be plugged into Cashfree’s MCP layer.

While the AI platforms themselves are unlikely to be exclusive to any one payment provider, Razorpay believes its merchant relationships could provide an edge. Mathur said merchants that Razorpay takes live on its AI-commerce integrations currently have some exclusivity arrangements. This could become a competitive edge in the long run. 

“The exclusive part is on the merchant side,” Mathur told Inc42. “The merchants that we are taking live only work with us.”

He said AI platforms will continue to support multiple payment providers, much like a merchant can host a website on Google while connecting any payment gateway. However, merchants are likely to work with only one or two payment providers for agentic commerce, with Razorpay aiming to secure those relationships early.

Mathur said Razorpay currently has the largest number of merchants live on these platforms, although the company declined to disclose updated numbers, saying adoption is scaling rapidly.

Trust, however, remains a common concern across the industry.

Cashfree’s CEO Akash Sinha earlier told Inc42 that although AI holds a huge promise for bringing efficiencies in the payments infrastructure business, the agentic commerce layer will likely face the challenge of consumers trusting agents with payments and data.

Mathur argues that Razorpay’s underlying payment architecture has been designed to ensure users remain in control of every transaction. According to him, AI models such as ChatGPT do not receive customers’ payment credentials, and every transaction continues to require user authorisation through NPCI’s UPI infrastructure.

In practice, the shopping flow begins with a user discovering products through an AI assistant. Once a purchase is initiated, the checkout is handed over to Razorpay’s payment infrastructure, which uses NPCI’s UPI capabilities—including UPI Circle and UPI Reserve Pay—to complete the transaction.

While the shopping experience remains conversational, payment authorisation still occurs through the user’s own UPI account and applicable two-factor authentication requirements, rather than through the AI assistant itself.

“It’s not like you give a customer’s details and let the agent shop and the customer has no control,” Mathur told Inc42.

Mathur said Razorpay’s integration has also been designed around two key compliance requirements: data residency and customer consent. “Payment data should not go to LLMs,” he said, adding that Razorpay uses the UPI Reserve Pay protocol to ensure that payment data does not touch the LLM at any point during the transaction.

“The way we have built our integration is we are using the Reserve Pay protocol which ensures that the payment data doesn’t touch the LLMs at any point of time,” Mathur said.

The second layer is consent. 

According to Mathur, payments must either be backed by pre-consent from the customer or require two-factor authentication. “Both of those are mandated,” he said, adding that ensuring compliance and governance while enabling payments through AI platforms is part of Razorpay’s role as the payment infrastructure provider.

The broader regulatory framework around AI-led commerce, however, is still evolving as more participants enter the transaction flow

Why Brands Are Joining Early

The early adopters are unsurprisingly digital-first brands.

Notably, customer acquisition has become one of the biggest pain points for D2C brands as advertising costs continue to rise across Meta and Google, and ecommerce marketplaces continue to charge high commissions amidst huge demand.

Razorpay says it is not yet charging merchants an additional platform fee during the early testing phase as it evaluates adoption and product-market fit. It didn’t reveal whether standard MDR or gateway charges will still apply on these transactions, or what the merchant’s own integration cost will be. 

For now, the company is focused on building adoption rather than revenue. Mathur said the eventual commercial model could involve a SaaS or distribution fee charged to merchants, but stressed that Razorpay is yet to determine the appropriate model.

The focus is on the adoption curve, not really on revenue in this area because it’s very early, Mathur told Inc42. 

“The simplest way would be, of course, like the way you charge a SaaS or a distribution fee from merchants. But that’s just me guessing right now. Unless we see scale, I don’t think we’ll focus on monetisation in this domain,” he added.

Unlike conventional online stores, AI commerce requires merchants to expose structured product catalogues, pricing information, inventory and payment workflows in formats AI assistants can understand.

“For many smaller merchants, building those capabilities independently would be difficult. Razorpay is attempting to abstract that complexity,” Mathur told us.

Mathur said the company is working with merchants across the spectrum, from small D2C brands to large marketplaces, with the objective of making it easier for them to go live on AI platforms without significant time or engineering investment.

The fintech giant believes this lowers the barriers for thousands of businesses already using its payment stack.

Beyond Payments, Towards Commerce Infrastructure

The ChatGPT partnership is only one part of Razorpay’s broader AI strategy.

Mathur revealed that roughly 200 businesses are already using the company’s Agent Studio platform in beta, deploying AI agents across reconciliation, abandoned-cart recovery, subscription recovery and finance operations.

The company has also begun introducing more sophisticated capabilities, including memory that allows agents to remember previous customer interactions and merchant-controlled customisation that determines how aggressively agents should pursue abandoned customers.

Interestingly, Razorpay has not started charging merchants for Agent Studio.

“We don’t even know what is the right way to charge for it,” Mathur admitted, adding that the company first wants to understand the value AI creates before determining commercial models.

That also leaves open broader questions around the economics of Razorpay’s AI strategy. 

Building AI infrastructure like agent orchestration, merchant integrations and conversational commerce capabilities that requires investment.

The economics of Razorpay’s broader AI strategy remain nascent. The company did not disclose a specific financial outlay for its AI stack, and one assumes that building a platform like this would have required significant investment. 

 “Investment is significant in terms of mostly engineering effort. You need to have a dedicated team that’s focused on agentic commerce that’s building for it consistently and shipping out services for that.”

Razorpay’s ambition also extends beyond ChatGPT. Mathur said the company is building a distribution layer across multiple agentic touchpoints, including merchant websites, independent agent platforms and large language model platforms.

“We are building a distribution layer across multiple agentic touchpoints,” Mathur said, adding that the company’s focus is on enabling agentic commerce in different forms rather than betting on a single AI platform.

Can ChatGPT Become India’s Next Shopping Mall?

The answer remains uncertain. Today’s ecommerce ecosystem is still dominated by dedicated apps and marketplaces.

Consumers are accustomed to browsing images, comparing reviews and discovering products visually — experiences that conversational interfaces are only beginning to replicate.

Trust is another hurdle. Many consumers may hesitate to allow AI assistants to complete financial transactions on their behalf.

Mathur argues similar doubts came up during the early years of ecommerce. Consumers initially purchased low-value products before gradually trusting digital commerce for larger transactions. He expects AI-led shopping to follow a comparable trajectory.

If that shift happens, ChatGPT and similar assistants could become meaningful discovery and commerce channels for brands. That possibility explains why Razorpay is investing ahead of the market reaching scale.

“We’ll have to scale it to a point where enough and more customers are transacting to the point that we say, hey, now we need to monetise it,” he said. “Right now we’re in the adoption phase of the journey. So 100% focus is on adoption.”

Early signals nevertheless suggest that the industry is preparing for that possibility. Retail giants such as Nykaa have begun measuring their visibility across AI answer engines, while payment companies including Razorpay and Cashfree are building different layers of infrastructure for conversational commerce.

Whether AI chatbots like ChatGPT or Claude ultimately become meaningful shopping destinations or remain a complementary discovery channel will depend on how quickly Indian consumers adopt AI-led commerce. Given the bullishness of Indian retailers and ecommerce enablers right now, that tension could define the future course of ecommerce. 

[Edited By Nikhil Subramaniam]

 

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