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Global tech companies and local start-ups are looking to unlock lucrative new markets in India with artificial intelligence platforms adapted for the vast range of languages and industries in the world’s most populous country.
Microsoft, Google and start-ups including Silicon Valley-backed Sarvam AI and Krutrim — founded by Bhavish Aggarwal of Indian mobility group Ola — are all working on AI voice assistants and chatbots that function in languages such as Hindi and Tamil. The tools are aimed at fast-growing Indian industries, such as the country’s large customer service and call centre sector.
India has 22 official languages, with Hindi the most widespread, but researchers estimate the languages and dialects spoken by its 1.4bn people rise into the thousands. Google on Tuesday launched its Gemini AI assistant in nine Indian languages.
Microsoft’s Copilot AI assistant is available in 12 Indian languages, and the company is working on other projects tailored for India, including building “tiny” language models at its Bengaluru-based research centre. These smaller alternatives to the expensive large language models underpinning generative AI can run on smartphones rather than the cloud, making them cheaper and potentially better suited to countries like India where connectivity can be limited.
Microsoft wants to “make [AI] simple and easy to use and get it to the hands of all these customers and partners”, Puneet Chandok, president of Microsoft for India and south Asia, told the Financial Times. He added that this involved “contextualising it for the Indian context, making it more relevant, more precise”.
Microsoft is also partnering with Sarvam AI. The Bengaluru-based company founded only last year is developing a “full stack” of generative AI tools for Indian businesses. The start-up has raised $41mn from investors including Peak XV, Sequoia’s former India arm, and Menlo Park-based Lightspeed Venture Partners.
Lightspeed partner Hemant Mohapatra said investing in local AI companies was becoming more important as governments seek to develop “sovereign AI” that is trained and stored within their borders.
“The AI supply chain is beginning to fragment,” said Mohapatra. “If you’re training a foundation model in India on Indian citizen data, audio, video, text, different languages, then it has to be an Indian company, focused on Indian use cases, Indian-domiciled, Indian founders and so on.”
Instead, companies such as Sarvam AI are focusing on adapting existing LLMs for Indian languages and using voice data instead of text. This makes them more effective in a country where many prefer to communicate through audio messages rather than in writing.
“There’s still a massive gap between these underlying models and real-world use cases in countries as complex as India,” said Lightspeed partner Bejul Somaia. “In a market like India, you’re going to need to have a little bit of an ecosystem that springs up to enable companies to use the underlying model capabilities.”
Tanuja Ganu, a manager at Microsoft Research in Bengaluru, said an additional benefit of testing new technologies and tools in a country of India’s size and diversity was that they could be exported elsewhere.
“It’s using India as a test bed and validating some of the technology in India and seeing how we can expand it to other parts of the world,” she said.
