Key Points

The partnership brings together IBM's expertise in AI, data governance and model training with BharatGen's mandate to build inclusive, India-centric AI systems. The goal is to create sovereign AI models rooted in local languages, values and contexts, while expanding their applications across education, agriculture, healthcare, banking and citizen services.

"With IBM's strength in enterprise-grade platforms and our commitment to public-good AI, we are on a path to drive transformative solutions for empowering India's digital journey across domains such as agriculture, finance, education, and governance," said Prof. Ganesh Ramakrishnan of BharatGen. He added that the company has been building sovereign AI models and the ecosystem that reflects the linguistic richness, cultural nuances, and diverse needs of our people.

As part of the collaboration, BharatGen and IBM will work on developing solution templates for Indic use cases. These will combine BharatGen's models and datasets with IBM's AI technologies, including its Granite models. The joint effort also plans to create demonstrations and use case templates on IBM Watsonx and Red Hat OpenShift AI.

In addition, the initiative will focus on building a scalable data pipeline using IBM's open-source tools, enhanced with Indic-specific capabilities to improve data preparation. It will also implement a governance framework from IBM's enterprise-scale methodology to support responsible AI development. The collaboration will further work on establishing new benchmarks for Indic languages and exploring advanced architectures for generative AI.

Sandip Patel, Managing Director, IBM India and South Asia, said, "At IBM, we are committed to support the creation of open, trusted AI that solves real-world problems. Through our collaboration with BharatGen, we aim to advance sovereign AI capabilities that reflect India's diversity and deliver meaningful impact across sectors."

BharatGen's roadmap for LLMs and foundation models is designed to address both national and commercial requirements. A key focus is on including underserved Indian languages and dialects beyond the most widely spoken 12-22, to ensure broader digital participation and equity.

- ANI