BharatGen & Sarvam sit at the top of this stack. Led by CEO Rishi Bal and founded by Ganesh Ramakrishnan, BharatGen is an IIT Bombay-anchored consortium that secured the largest GPU allocation under the IndiaAI Mission. Its flagship release, Param2 17B, is a 17-billion-parameter multilingual model built from scratch using an MoE architecture and trained extensively on Indian datasets. It supports 22 Indian languages and spans reasoning, mathematics, code, speech, text and vision. Over 60 engineers across nine academic institutions are working towards a larger target: a trillion-parameter model—a philosophy that Ramakrishnan calls "Virasat bhi aur vikas bhi". Sarvam AI offers a contrasting lesson. Founded by Vivek Raghavan and Pratyush Kumar, Sarvam faced criticism for its earlier 24B model but has since recalibrated. At the India AI Impact Summit, it launched Sarvam 30B and Sarvam 105B, signalling a renewed push at the large-model layer while deepening its Indic focus. It also launched Indus, a chatbot positioned to compete with ChatGPT, which has seen strong domestic reception. Bulbul V3, its text-to-speech model, topped a blind study with over 20,000 votes across 11 languages. Sarvam Vision reported 84.3% accuracy on messy documents across 22 Indic scripts. Besides, Sarvam has signed an MoU with the Odisha government for a sovereign AI park, partnered with Tamil Nadu, and signed an LoI with Maharashtra to build sovereign AI infrastructure across the state to create 20 MW of AI-optimised compute capacity. Then there's Gnani.ai. Led by Ganesh Gopalan, it launched a 5-billion-parameter voice-to-voice model, Inya VoiceOS, along with Inya.ai, a no-code agentic platform. Enterprises report 4-6% higher collection rates, nearly 2x loan disbursals and 80% faster fraud detection using voice biometrics. This followed the launch of its Vachana STT and TTS models at the Summit. Others are pursuing sharper specialisation. Genloop, led by CEO Ayush Gupta, is building three 2-billion-parameter models under the IndiaAI Mission: Yukti for multilingual reasoning, Varta for edge deployment in healthcare and agriculture, and Kavach as a guardrail model to secure AI inputs and outputs for Indians. Genloop argues that Western public models are expensive and linguistically misaligned, and claims its enterprise analytics platform is being piloted by firms including Lenskart and Emeritus. Meanwhile, Soket AI Labs, led by CEO Abhishek Upperwal, is developing Project EKA—a 120-billion-parameter open source model trained on India-centric datasets. Its roadmap scales from 1B to 120B, with air-gapped and on-device deployments planned for sensitive sectors. The company speaks openly about national security risks of relying on foreign models in defence contexts. Its COOM framework promises transparent updates and energy-efficient training. ZenteiQ moves the conversation to factories and labs. Founded by Prof Sashikumaar Ganesan, it builds physics-aware AI for engineering and industrial intelligence—from thermal optimisation and battery modelling, to semiconductor design and simulation acceleration. The argument is that sovereignty is not only about chatbots, but about control over AI embedded in manufacturing and energy infrastructure. |
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