Razorpay Scales Merchant Outreach Using ElevenLabs Voice Agents.

Razorpay, one of India's largest payments platforms serving millions of merchants, has deployed AI voice agents from ElevenLabs to scale its outbound merchant engagement. The company announced the deployment in a LinkedIn post detailing how the voice agents now proactively call merchants to recover churned accounts, drive feature adoption, and communicate during incidents.

The voice agents operate in Hinglish, a blend of Hindi and English widely spoken across India's business community, and capture structured insights from every conversation. This turns what was previously manual outreach into a scalable, repeatable process, addressing a core challenge for platforms managing millions of merchant relationships.

Reaching merchants at the right moment has historically been difficult to do consistently at scale. For a platform like Razorpay, which processes billions in payments and supports diverse merchant segments, timing and personalization matter. A churned account might be recoverable with the right intervention, and a merchant confused about a new feature could become a power user with proper guidance.

Razorpay's deployment of ElevenAgents allows the company to tackle these scenarios systematically. Voice agents can initiate calls based on triggers such as inactivity, feature non-adoption, or service incidents, then handle the conversation and log outcomes without human involvement. The agents are built on ElevenLabs' conversational AI platform, which recently launched Guardrails 2.0 to improve control and accuracy in enterprise deployments.

The Hinglish capability is particularly important for Razorpay's merchant base. Many small and medium-sized businesses in India operate in bilingual environments, and a voice agent that can seamlessly switch between Hindi and English removes friction from customer interactions. This mirrors ElevenLabs' broader push into multilingual voice AI, including recent partnerships with IBM to expand enterprise language support.

Beyond automation, Razorpay's implementation emphasizes structured data capture. Each call generates insights that feed back into the platform, helping the company understand why merchants churn, which features cause confusion, and how incidents affect different segments. This data layer transforms voice agents from cost-saving tools into strategic assets for product and operations teams.

ElevenLabs has positioned ElevenAgents as a platform for enterprise-scale voice automation, with recent deployments at companies like Klarna and Revolut demonstrating similar use cases in customer support and engagement. The Razorpay case study adds a new dimension by focusing on proactive outbound calling rather than inbound support, a harder problem that requires agents to handle cold outreach, objections, and varied merchant contexts.

Razorpay directs readers to a full case study via the link in the LinkedIn post comments, suggesting the deployment includes additional technical details and performance metrics not disclosed in the announcement.

The Razorpay deployment reflects a broader trend of enterprises moving voice AI from pilot projects to production workloads. ElevenLabs has been building out its enterprise offering rapidly, including government-focused solutions and on-premise deployment options for organizations with strict data residency requirements.

For platforms like Razorpay that manage millions of relationships, voice agents offer a way to maintain engagement at a scale that human teams cannot match. As more companies publish case studies and performance data, the economics of voice AI in outbound engagement will become clearer, potentially accelerating adoption across fintech, e-commerce, and other merchant-facing industries.

ElevenLabs has not disclosed pricing or contract details for the Razorpay deployment.