India’s Ringg Secures Peak XV Funding to Expand Voice AI Beyond Phone Calls

Ringg, a voice AI startup, is gaining momentum in the Indian market, with a recent study from Truecaller revealing that over 76% of consumers in India prefer phone calls for communicating with businesses. This trend highlights a significant opportunity for automation in customer support and outreach using voice AI technology. Currently, Ringg handles around 20 million call attempts monthly and continues to believe in this growth, as evidenced by their recent funding acquisition.

In a new development, Ringg has successfully secured $10 million from Peak XV Partners as part of an extension to its Series A funding. This follows an earlier raise of $5.5 million, bringing the total from this funding round to $15.5 million.

Initially launched as a text-to-speech platform under the name DesiVocal, Ringg shifted focus to providing voice AI agents for businesses due to the high costs of developing its own speech models. The fintech company Cred was its first major client, and since then, Ringg has expanded its portfolio to include well-known startups such as Flipkart, Practo, Groww, and PolicyBazaar.

Co-founder Siddharth Tripathi explained that while their early efforts revolved around simple applications like outbound calling and loan collection, the company recognized the need to build more value-centric solutions. Consequently, Ringg is now focusing on more intricate processes such as appointment scheduling for healthcare clinics, recovering abandoned carts for e-commerce platforms, and conducting onboarding/KYC checks for fintech applications.

The company’s voice agent is currently operational in approximately 1,200 clinics through its partnership with Practo, assisting patients in booking appointments and following up post-visit.

Voice calls account for more than 70% of Ringg’s revenue; however, the startup is diversifying into other communication channels, including chat and WhatsApp. For notable clients like Shell, Ringg is also developing automation for browser-based support requests.

Tripathi emphasized that the company aims to present itself as a comprehensive platform for agents that drives outcomes, rather than merely functioning as voice agents for enterprises.

The majority of Ringg’s clientele is based in India, with some beyond the region in the Middle East and the U.S. However, rather than targeting direct sales to U.S. companies, Ringg plans to collaborate with global capability centers in India that service multinational corporations for back-office support, thus complementing human efforts with automated solutions.

Currently, Ringg is focused on developing its own speech recognition and generation models, aspiring to eventually manage the complete voice technology stack, including both infrastructure and deployment. For now, however, its offerings act as an orchestration layer, directing tasks to various models based on specific use cases.

Peak XV’s principal, Rishen Kapoor, noted that Ringg’s origins as a research lab contribute to its ability to tackle complex use cases effectively. He praised the startup’s advanced technical skills, emphasizing their capability to efficiently manage higher-value tasks like merchant onboarding and tier-one and tier-two support.

The voice AI landscape in India is highly competitive, featuring various model creators such as Deepgram, ElevenLabs, and Cartesia, alongside regional players like Sarvam and Smallest.ai. Startups focusing on orchestration like Bolna and Blue Machines also share the operational space that Ringg occupies, while companies like Gnani and Arrowhead specialize in financial services.

This layered ecosystem—spanning model developers, orchestrators, and application-focused players—underlines the significance of owning customer relationships and achieving desired outcomes in the AI-driven market.

Currently, Ringg employs around 40 individuals, with over 15 new hires joining in the last three months. The company is on the lookout for forward-deployed engineers who possess both technical and product management skills, along with researchers aimed at reducing operational costs for its models.