Bodhan AI releases open-weight Indian-language AI models for education

Open AI models and sovereign APIs enable ecosystem partners to build multilingual solutions, while TutorBot and Teacher Assistant Bot bring AI support to students and teachers

Bodhan AI, the Centre of Excellence in AI for Education incubated at IIT Madras, has launched four foundational artificial intelligence (AI) models for Indian languages to build a sovereign technology layer for the multilingual education ecosystem.

 

Developed in partnership with AI4Bharat, the models are being made available to the wider technology and education ecosystem as Digital Public Goods, through open-weight releases and hosted application programming interfaces (APIs) on a sovereign Digital Public Infrastructure.

 

“India’s AI journey cannot be built on technology alone. It must be built on technology that understands India. The launch of these voice and vision models is an important step towards creating sovereign Digital Public Infrastructure for AI in education that can serve our linguistic diversity and enable innovation at scale," said V Kamakoti, director, IIT Madras.

 

 

Bodhan AI’s model strategy forms part of the broader Bharat EduAI Stack, envisioned as a sovereign digital public infrastructure for education. While, AI4Bharat brings expertise in Indian languages AI, multilingual modelling and datasets. These voice and vision models are an early flagship output, designed to enable development of AI solutions across Indian languages.

 

Bodhan AI, which is funded by the Ministry of Education, is releasing a suite of AI models spanning four core capabilities: speech recognition, speech generation, machine translation and Optical Character Recognition (OCR).

 

Edtech companies can integrate Indian language AI capabilities into their products through APIs without having to develop foundational models from scratch. Startups and technology companies can access open-weight models, adapt them and fine-tune them for new applications and user groups. Researchers and universities can use the models as a foundation for further research, experimentation and development in Indian-language AI.

 

The models are trained and optimised using NVIDIA Nemotron open models and libraries, including the NVIDIA NeMo framework for automatic speech recognition (ASR), machine translation (MT) and OCR. Bodhan post-trained NVIDIA Nemotron 3.5 ASR to support Indian languages, including regional dialects and accents.

 

ASR can allow a student to speak to an AI tutor in their preferred language rather than having to type in English. TTS can enable an AI system to respond naturally in an Indian language. OCR can allow educational AI systems to understand textbooks, worksheets, documents and handwritten answers, while Bodhan-Translate can help educational content move across Indian languages.

 

"By making these capabilities available to the wider ecosystem, Bodhan AI is helping create the foundations for an education system where every student and teacher can access the benefits of AI, irrespective of the language they speak,” Kamakoti said.

 

Both NVIDIA and Bodhan AI are collaborating on datasets, training recipes and evaluations to support future foundational models for Indian languages.

 

“Bodhan AI aims to build with the ecosystem, not compete with it. We built these voice and vision models, and made them accessible as Digital Public Goods on a Digital Public Infrastructure, so that efforts across the country don't remain fragmented. Instead, there is one common layer that can power all Edu AI in India, without every institution having to duplicate the same work," said Mitesh Khapra, principal investigator at Bodhan AI.

 

For Bodhan AI, the ultimate purpose of these foundational models is to make AI more accessible to teachers and students, particularly those who interact with technology in Indian languages, he added.

 

The Centre of Excellence is also launching ‘Student TutorBot’ and ‘Teacher Assistant Bot’, bringing multilingual AI-powered learning and teaching support directly to students and teachers. The models will also form part of the technology foundation powering Bodhan AI’s own education applications, including Student TutorBot and Teacher Assistant Bot, while remaining available for others to build upon. This creates a model in which the same foundational capabilities can be reused across multiple applications and institutions, reducing duplication and enabling a broader ecosystem of innovation.

 

Student TutorBot is an AI-powered learning companion for students in Classes 6-12, designed around National Council of Educational Research and Training (NCERT) and State Council of Educational Research and Training (SCERT) curricula to provide structured, personalised learning support beyond the classroom. Students can ask questions through text or voice across 22 Indian languages, with TutorBot using their textbook content to provide explanations, examples and assessments. The model will guide students step-by-step through problems, using interactive tools and a digital canvas for diagrams, calculations and working. Students can also be assessed on the same curriculum content, with their demonstrated understanding informing subsequent learning support.

 

The Teacher Assistant Bot is a pan-India AI workspace designed to help teachers plan, create, assign, assess and refine classroom work more efficiently, while keeping the teacher firmly in control. Teachers can generate lesson plans, worksheets, quizzes, homework and revision sheets by specifying parameters such as grade, subject, topic, duration, difficulty and assessment requirements, and can also upload student work for evaluation with specific marking criteria.

 

Importantly, every AI-generated output is treated as a starting point for the teacher to review, edit, regenerate or discard, rather than an automatic classroom decision. The Teacher Assistant Bot is, therefore, positioned not simply as an AI content generator, but as a working environment that helps teachers turn their teaching intent into classroom-ready work, faster.

 

Data privacy and responsible deployment are foundational to the initiative. Bodhan AI’s architecture will incorporate data anonymisation protocols and compliance with applicable national education data frameworks, with the hosted API infrastructure designed around a sovereign deployment approach.

 

This will provide institutions and ecosystem partners greater control over how AI capabilities are deployed, while supporting India’s requirements around data governance, privacy and security.