Partnership · AI & Deep Tech

Mahindra Finance deploys Sarvam AI voice agents across operations

By Startup Enthusiast · 10 September 2026

What they do

Sarvam AI provides a full-stack sovereign artificial intelligence platform built for Indian languages, culture, and context

Mahindra Finance has expanded its collaboration to deploy voice artificial intelligence across sales, collections, and employee engagement

The deployment integrates voice agents with internal machine learning models to handle over one crore calls in 12 languages

Mahindra & Mahindra Financial Services has expanded its collaboration with Sarvam AI to integrate voice artificial intelligence into its core operations.
Voice agents operate in 12 Indian languages to handle interactions across sales, collections, and employee engagement.
The initiative has successfully surpassed ten million phone interactions across various semi-urban and rural areas.
Mahindra Finance combines the voice agents with internal machine learning models to identify customer opportunities and run automated campaigns.
Every single conversation undergoes recording and evaluation through specialized analytical workflows linked straight to underlying loan servicing and customer management databases.
The technology is also utilized to gather direct operational feedback from field employees to give leadership visibility into frontline realities.

Financial institutions in India face the challenge of scaling customer interactions while maintaining local language connections across diverse regions.
Integrating voice agents directly into business workflows allows companies to turn customer conversations into structured, actionable inputs for subsequent business actions.

Sarvam AI builds a full-stack sovereign artificial intelligence platform developed and operated entirely within India.
The company offers voice agents, text-to-speech, speech-to-text, translation, and document digitisation tools across multiple Indic languages.
Products serve enterprises, developers, and government services requiring population-scale applications and conversational agents.

Product: Foundation models and agentic AI systems with voice capabilities and enterprise applications
Customers: Enterprise customers across finance, aviation, telecom and government sectors
How it makes money: SaaS and licensing model for AI models and enterprise AI applications
What sets it apart: India-built sovereign AI stack with focus on cost-effective deployment and localization