# AI and digital platforms: Follow one offering through the chain Model builders and apps selling AI as assistants, APIs and copilots, not hardware Source page: https://www.materialinsights.org/industries/ai_platforms/story/ #### Follow one offering through the chain **6** Example story · 7 steps · India ### Sarvam's Indian-language AI model, built in India Follow one answer in an Indian language back through the app, the model, public data, subsidised GPUs and the chips beneath. 1 / 7 · AI chips #### Chips designed in America, made in Taiwan **80-90%**Nvidia share of AI accelerator revenue Every answer is computed on graphics processors, mostly Nvidia's, designed in California and fabricated and packaged by TSMC in Taiwan. Analysts estimate Nvidia took 80-90% of AI accelerator revenue in 2025. Sarvam's models were built on Nvidia hardware hosted in India, so the costliest and most concentrated part of this chain sits abroad.^[1](https://siliconanalysts.com/analysis/nvidia-ai-accelerator-market-share-2024-2026) **Constraint** Supply depends on one foundry's advanced packaging capacity in Taiwan, and US export controls decide which countries may buy the top chips. [Si Silicon](https://www.materialinsights.org/commodities/silicon/)[Cu Copper](https://www.materialinsights.org/commodities/copper/)[Au Gold](https://www.materialinsights.org/commodities/gold/)[He Helium](https://www.materialinsights.org/commodities/helium/)[ESG Electronic specialty gases](https://www.materialinsights.org/chemicals/electronic_gases/)[Semiconductors](https://www.materialinsights.org/industries/semiconductors/) 2 / 7 · Compute infrastructure #### Subsidised GPUs on Indian clouds **₹65/hr**subsidised IndiaAI GPU rate The chips sit in Indian data centres, such as Yotta's Shakti Cloud, rented out by the hour. Under the IndiaAI Mission more than 38,000 GPUs had been onboarded by February 2026, offered at about ₹65 an hour, nearly a third of the global average, the government says. In April 2025 the government said it would allocate Sarvam 4,000 GPUs for six months.^[2](https://static.pib.gov.in/WriteReadData/specificdocs/documents/2026/feb/doc2026210784401.pdf)^,^[3](https://india.entrepreneur.com/en-in/news-and-trends/sarvam-ai-to-build-indias-first-homegrown-genai-platform/490709)^,^[4](https://www.iea.org/reports/energy-and-ai/energy-demand-from-ai) **Constraint** Data centres used about 415 TWh, 1.5% of world electricity, in 2024; grid connections, transformers and cooling water limit new campuses. [Cu Copper](https://www.materialinsights.org/commodities/copper/)[H₂O Water](https://www.materialinsights.org/commodities/water/)[Tc Thermal coal](https://www.materialinsights.org/energy/thermal_coal/)[DC Data centres](https://www.materialinsights.org/energy/e_data_centres/)[LFP Lithium iron phosphate batteries](https://www.materialinsights.org/energy/e_li_lfp/)[Data centres and cloud](https://www.materialinsights.org/industries/data_centres/)[Electrical equipment](https://www.materialinsights.org/industries/electrical_equipment/)[Computers and electronics](https://www.materialinsights.org/industries/computers_electronics/) 3 / 7 · Data, talent and capital #### Indian-language data, gathered and shared **7,541**datasets on AIKosh, February 2026 A model is only as good as its text and speech. The web holds far less material in Indian languages than in English, so public platforms help: the government's AIKosh listed 7,541 datasets and 273 models across 20 sectors by February 2026, and Bhashini supports more than 36 languages. Labs then clean, label and add licensed and synthetic data.^[2](https://static.pib.gov.in/WriteReadData/specificdocs/documents/2026/feb/doc2026210784401.pdf) **Constraint** Scarce high-quality text in many Indian languages, and unsettled copyright rules on training data, limit what models can learn. [Media and entertainment](https://www.materialinsights.org/industries/media_entertainment/)[Software and IT services](https://www.materialinsights.org/industries/software_it/)[Education and research](https://www.materialinsights.org/industries/education_research/) 4 / 7 · Data, talent and capital #### Public money beside venture capital **₹10,372cr**IndiaAI Mission outlay, five years Training runs cost more than most Indian start-ups can raise. The IndiaAI Mission has an outlay of ₹10,371.92 crore over five years, approved in March 2024, and picked 12 foundation-model builders, including Sarvam and IIT Bombay's BharatGen, from more than 500 proposals. Venture investors fund the rest, but on a far smaller scale than in the US.^[2](https://static.pib.gov.in/WriteReadData/specificdocs/documents/2026/feb/doc2026210784401.pdf)^,^[5](https://hai.stanford.edu/ai-index/2026-ai-index-report/economy) **Constraint** The US attracted US$ 285.9 billion of AI investment in 2025; India's five-year mission totals about US$ 1.2 billion (calculated). [Finance: banking, insurance, markets](https://www.materialinsights.org/industries/finance/) 5 / 7 · Foundation models #### A 105-billion-parameter model from Bengaluru **105bn**parameters in Sarvam's larger model Sarvam, a Bengaluru start-up, trained its own models rather than adapting a foreign one. At the India AI Impact Summit in New Delhi in February 2026 it showed a 30-billion-parameter model for real-time conversation and a 105-billion-parameter model handling up to 128,000 tokens, both supporting all 22 scheduled Indian languages and built with IndiaAI, Yotta and Nvidia support.^[6](https://www.indiascienceandtechnology.gov.in/stihighlights/sarvam-ai-unveils-indigenous-multilingual-foundation-models-india-ai-impact-summit)^,^[5](https://hai.stanford.edu/ai-index/2026-ai-index-report/economy) **Constraint** Frontier labs spend far more: OpenAI's compute bill was about US$ 16.3 billion in 2025, so Indian models must compete on language and cost. [DC Data centres](https://www.materialinsights.org/energy/e_data_centres/)[Data centres and cloud](https://www.materialinsights.org/industries/data_centres/)[Education and research](https://www.materialinsights.org/industries/education_research/) 6 / 7 · Tooling and integration #### Wired into banks and public services **$439bn**world AI services spending, 2025 India's biggest AI strength is fitting models into other organisations' systems. IT services firms such as TCS and Infosys, and model makers themselves, connect models to documents, call centres and government portals, adding retrieval, security and testing. Gartner put worldwide spending on AI services at about US$ 439 billion in 2025, a field where Indian IT firms compete strongly.^[7](https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026) **Constraint** Clients can switch integrators within weeks, and AI coding tools may shrink the headcount-based billing on which Indian IT firms earn. [Software and IT services](https://www.materialinsights.org/industries/software_it/) 7 / 7 · Applications and platforms #### Vikram answers in your language **22**scheduled Indian languages supported The user meets the chain as a chatbot or voice assistant. Sarvam showed Vikram, a voice-first multilingual chatbot, at the February 2026 summit, plus a model it says reads documents in Indian scripts with over 84% accuracy (company claim). Every question runs the model again on rented GPUs, so serving millions of users is a running cost, not a one-off.^[6](https://www.indiascienceandtechnology.gov.in/stihighlights/sarvam-ai-unveils-indigenous-multilingual-foundation-models-india-ai-impact-summit) **Constraint** Every answer consumes inference compute, so without cheap GPUs and power, free Indian-language assistants struggle to cover their costs. [Software and IT services](https://www.materialinsights.org/industries/software_it/)[Data centres and cloud](https://www.materialinsights.org/industries/data_centres/)[Finance: banking, insurance, markets](https://www.materialinsights.org/industries/finance/) #### What the chain shows India can build its own language models on subsidised compute, but the chips, and most of the money, still come from abroad; its edge is services and languages. Sources 1. [Nvidia AI accelerator market share 2024-2026 (analyst estimates)](https://siliconanalysts.com/analysis/nvidia-ai-accelerator-market-share-2024-2026) Silicon Analysts, 2026 2. [Democratising AI in India: expanding access to AI resources, skills and technology nationwide](https://static.pib.gov.in/WriteReadData/specificdocs/documents/2026/feb/doc2026210784401.pdf) Press Information Bureau, Government of India, 2026 3. [Sarvam AI to build India's first homegrown GenAI platform in six months under IndiaAI Mission](https://india.entrepreneur.com/en-in/news-and-trends/sarvam-ai-to-build-indias-first-homegrown-genai-platform/490709) Entrepreneur India, 2025 4. [Energy and AI: Energy demand from AI](https://www.iea.org/reports/energy-and-ai/energy-demand-from-ai) International Energy Agency, 2025 5. [The 2026 AI Index Report: Economy](https://hai.stanford.edu/ai-index/2026-ai-index-report/economy) Stanford HAI, 2026 6. [Sarvam AI unveils indigenous multilingual foundation models at India AI Impact Summit](https://www.indiascienceandtechnology.gov.in/stihighlights/sarvam-ai-unveils-indigenous-multilingual-foundation-models-india-ai-impact-summit) India Science and Technology (Government of India), 2026 7. [Gartner says worldwide AI spending will total $2.5 trillion in 2026](https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026) Gartner, 2026 ## Other sections - [Overview](https://www.materialinsights.org/industries/ai_platforms/index.md) - [Where ₹100 goes](https://www.materialinsights.org/industries/ai_platforms/cost-mix/index.md) - [Price links with suppliers](https://www.materialinsights.org/industries/ai_platforms/price-links/index.md) - [Linked industries](https://www.materialinsights.org/industries/ai_platforms/linked-industries/index.md) - [Value chain](https://www.materialinsights.org/industries/ai_platforms/value-chain/index.md) - [Materials drawn on](https://www.materialinsights.org/industries/ai_platforms/materials/index.md) - [Chokepoints and risks](https://www.materialinsights.org/industries/ai_platforms/risks/index.md) - [Sources](https://www.materialinsights.org/industries/ai_platforms/sources/index.md)