Cashfree Payments has introduced Relay, a no-code AI agent designed to significantly reduce manual payment tasks for small and medium-sized businesses, marking a strategic move to diversify revenue streams and compete with rivals like Razorpay in the Indian fintech landscape.
Cashfree Payments has launched Relay, an AI agent built to automate routine payment tasks for small and medium-sized businesses, as Indian fintech firms look for new ways to monetise beyond core transaction processing. According to the company, the tool is designed to handle work such as retrying failed payments, recovering abandoned carts, confirming cash-on-delivery orders and managing disputes.
The Bengaluru-based company says SMBs can spend as much as 60 hours a week on payment operations, a burden it claims Relay can cut to about 45 minutes. Mayank Juneja, director of engineering at Cashfree Payments, told the company that merchants often rely on growth teams to chase customers who drop out at checkout or run into payment problems. Relay is meant to take over those follow-ups through voice or text, sometimes using incentives such as discounts to help close a sale.
Cashfree says the system is hosted on its own infrastructure and that merchant transaction data is not shared with outside AI providers. The company also describes Relay as a no-code workflow tool available through its merchant dashboard, with features that let businesses build automations visually or trigger prebuilt actions using plain language. It can also connect with channels including email, WhatsApp, Slack and Google Sheets.
The launch comes as payments companies in India increasingly explore agentic products, where AI does not just answer questions but performs tasks on behalf of a business. Cashfree has said Relay will initially be free, with outcome-based pricing planned later, tied to results such as recovered carts or resolved disputes. The move follows similar efforts by rivals, including Razorpay’s recent introduction of Vulcan, an AI model aimed at improving payment success rates and fraud detection.
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