AI’s English Problem—and Why We Should Care

Bhashini’s Delhi office was abuzz in the lead-up to February’s India AI Impact Summit. Building multilingual AI systems from the ground up is no easy task. The process of creating multilingual language datasets for 22+ Indic languages is often referred to by Bhasini CEO Amitabh Nag, as “stitching together by brute force.” The phrase captures the scale of the task: assembling vast volumes of speech, text, and translation data across dozens of languages and dialects, to create a pipeline for indigenous model development.

Launched in July 2022 under the aegis of the Digital India Corporation in the Ministry of Electronics and Information Technology, Bhashini’s core mission is to break language barriers across India. Since then, it has rapidly developed over 350+ open source AI models, 4,500+ language training datasets, and launched a co-creation platform bringing together governments, startups, and academia to ideate and build multilingual AI systems. Its models covering voice-first solutions and neural machine translation capabilities are already integrated across multiple government services.