What challenges did Sarvam AI face before AI implementation?

Lack of affordable, multilingual AI solutions for Indian businesses and agriculture. Significant language barriers preventing digital transformation across regions with diverse Indic languages. Limited access to sophisticated AI for small and medium enterprises due to high cost or technical complexity.

What was the impact of the AI solution?

Democratized access to conversational AI for business and agriculture across India. Reduced language and digital skill barriers for AI adoption in rural and enterprise settings. Enabled affordable, scalable voice-based automation for business processes.

Source

MicrosoftEvidence: Low25/100

Sarvam AI drives multilingual conversational automation for Indian business and agriculture

Use case typeMultilingual communicationUpdated Jun 13, 2026

Sarvam AI, based in Bengaluru, launched India's first open-source foundational AI model, Sarvam 2B, designed for Indic languages. With support from Microsoft partnerships and Indian government initiatives, Sarvam AI developed Sarvam Agents—multilingual, voice-enabled AI agents that automate customer service and other business functions across telephony, WhatsApp, and mobile applications. These agents are easily customizable using low-code tools, addressing local business problems and breaking language barriers across India’s diverse linguistic landscape. The technology allows affordable voice AI for agriculture, business, and customer service, and is accessible to a broad range of enterprises thanks to minimal technical requirements and low per-interaction costs.

Organization: Sarvam AI
Industry: Tech & Comms
Location: India
Published: August 2024

Reported outcomes

Strategic outcomes

New product / capabilityLaunched multilingual voice AI agentsMarket & geographic expansionReached businesses and agriculture across IndiaCustomer experience & trustReduced language barriers for usersScale & capacityEnabled scalable voice-based automation

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Sarvam AI
Provider: Microsoft
Maturity: Unknown
Linked source: linkedin.com

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Multilingual Voice-Enabled AI Agent for Customer Support
2Low-Code Conversational AI Automation
3AI-Powered Agriculture Advisory in Local Languages

Lack of affordable, multilingual AI solutions for Indian businesses and agriculture.
Significant language barriers preventing digital transformation across regions with diverse Indic languages.
Limited access to sophisticated AI for small and medium enterprises due to high cost or technical complexity.

Developed Sarvam 2B, a multilingual large language model tailored for Indic languages.
Launched Sarvam Agents: customizable, voice-enabled AI agents delivered through multiple channels (telephony, WhatsApp, apps).
Used Microsoft technology and low-code tools for rapid agent development in Hindi, Urdu, English, and more.

Technologies

AI Microsoft

Democratized access to conversational AI for business and agriculture across India.
Reduced language and digital skill barriers for AI adoption in rural and enterprise settings.
Enabled affordable, scalable voice-based automation for business processes.

Sources & evidence1

Evidence: Low25/100Evidence strength