Hyderabad-based AM Intelligence — founded by the promoters of renewable energy major Greenko Group — has placed a binding order for 9,000 Nvidia Vera Rubin NVL72 rack-scale systems, positioning it among Asia's first adopters of the platform. The order sits inside an $8 billion plan to build 1 gigawatt of AI compute capacity, with the Hyderabad facility, delivery due Q1 2027, aimed at running trillion-parameter models and agentic AI workloads.
Explore India's AI landscape — population, workforce sectors, state-level data.
| # | Model | Org | Indic | Global | |
|---|---|---|---|---|---|
| 1 | Sarvam-105B INDIA | Sarvam AI | 🇮🇳 | 90% | 18% |
| 2 | Sarvam-30B INDIA | Sarvam AI | 🇮🇳 | 89% | 16% |
| 3 | IndicTrans2 / Airavata INDIA | AI4Bharat (IIT Madras) | 🇮🇳 | 76% | 10% |
| 4 | BharatGen Param2-17B INDIA | BharatGen (IIT Bombay) | 🇮🇳 | 72% | 12% |
| 5 | Hanooman (up to 40B) INDIA | SML x BharatGPT | 🇮🇳 | 68% | 11% |
| 6 | Gnani.ai Voice LLM INDIA | Gnani.ai | 🇮🇳 | 63% | 9% |
| 7 | Krutrim-3 INDIA | Ola Krutrim | 🇮🇳 | 60% | 8% |
| 8 | Project Indus (8B) INDIA | Tech Mahindra | 🇮🇳 | 58% | 9% |
Virat Kohli played his last T20 International on June 29, 2024 — the T20 World Cup final against South Africa in Barbados, which India won by 7 runs. Kohli scored 76 off 59 balls in the final, his best knock of the tournament, fittingly ending on a high note with the trophy in hand.
Matches: 125 | Innings: 107 | Runs: 4,188 | Average: 48.69 | Strike Rate: 137.04
Hundreds: 1 | Fifties: 38 | Highest Score: 122* vs Afghanistan (2022)
Not Outs: 21 | 4s: 397 | 6s: 114
2010-2016 (Building Phase): 44 matches, 1,366 runs at 36.94. Kohli was finding his T20I groove while already dominating ODIs and Tests.
2016-2022 (Peak Phase): 58 matches, 2,100 runs at 52.50, SR 140+. This was Kohli at his devastating best — anchoring innings while maintaining elite strike rates.
2022-2024 (Final Phase): 23 matches, 722 runs at 45.12. Included the World Cup final knock. Slightly reduced volume but maintained average, accepting a slightly different role.
Kohli retires as T20I cricket's most consistent run-scorer with 38 fifties (most by any batter). His average of 48.69 with a SR of 137+ across 125 matches represents a combination of consistency and aggression that no other T20I batter has matched at similar volume.
Overall T20I Economy: Bumrah 6.27 | Rashid Khan 6.45 | Josh Hazlewood 7.12 | Shaheen Afridi 7.68 | Pat Cummins 7.82
Bumrah's 6.27 economy in T20Is since 2024 is the best among all pace bowlers who have bowled 100+ overs in the format.
Powerplay (0-6): Bumrah 5.8 econ (elite) — compared to Hazlewood 6.9, Cummins 6.5. Only spinner Rashid Khan (5.2) is more economical in powerplay T20Is.
Death Overs (16-20): Bumrah 8.2 econ (exceptional for pace) — compared to Arshdeep Singh 9.1, Jofra Archer 8.7, Haris Rauf 9.4. Bumrah's yorker proficiency gives India a death-bowling edge.
Bumrah's selective T20I availability (managed by BCCI to protect Test career) means fewer matches but higher per-match impact. His wickets-per-match ratio of 1.8 is among the top 3 globally for pace bowlers since 2024.
Wankhede Stadium, Mumbai: Avg 1st innings: 172 | Pace wickets: 58% | Toss win-chase correlation: 52% | Short square boundaries favor power hitters.
M.A. Chidambaram, Chennai: Avg 1st innings: 163 | Spin wickets: 47% (highest IPL venue) | Slow, turning pitches historically assist CSK's spin-heavy bowling. Dew factor moderate.
Narendra Modi Stadium, Ahmedabad: Avg 1st innings: 178 (highest) | True batting surface | Drop-in pitches offer even bounce. Capacity 132,000 creates unmatched atmosphere.
Eden Gardens, Kolkata: Avg 1st innings: 168 | Balanced pitch | Evening dew is a significant factor — teams winning toss choose to bowl 72% of the time.
M. Chinnaswamy, Bangalore: Avg 1st innings: 176 | Short boundaries + altitude = six-hitting paradise | Pace-friendly in first hour, flattens out. RCB's home fortress in 2025 title run.
Across all IPL venues, teams batting second win 53.2% of matches (2022-2025). Venues with highest dew advantage: Eden Gardens (58%), Arun Jaitley Stadium Delhi (56%), Wankhede (55%). This makes toss a significant factor — especially in evening starts.
Suryakumar Yadav assumed T20I captaincy full-time after the 2024 T20 World Cup retirement of key seniors. In approximately 28 T20Is as captain (Jul 2024 – Feb 2026), India have won roughly 19, maintaining a win percentage near 68%.
Sri Lanka T20I series (Jul 2024): India won 3-0 (SKY's first full series as captain).
South Africa away (Nov 2024): Lost 1-3 in a tough away assignment.
England T20Is (Jan 2025): Won 3-2 at home in a closely fought series.
Bangladesh (2025): Clean sweep 3-0.
SKY's captaincy is defined by aggressive field placements in the powerplay, rotating bowlers based on matchup data, and batting-first preference (60% of tosses chose to bat). His own batting has dipped slightly (avg 28.5 as captain vs 36.2 when not captain) — the weight of dual responsibility.
Win rate above 65% makes SKY one of India's most successful T20I captains statistically. The real test comes in the England away series (July 2026) where conditions will challenge India's spin-heavy approach.
India and Australia have emerged as the two most lethal pace attacks in T20I cricket. Here's how they compare across phases:
India pace unit: 7.4 econ (led by Bumrah 6.27, Arshdeep 8.1, Siraj 7.9)
Australia pace unit: 7.8 econ (led by Hazlewood 7.12, Cummins 7.82, Starc 8.2)
Powerplay (0-6): India 6.8 vs Australia 7.1 — Bumrah's 5.8 powerplay economy gives India a clear edge.
Middle Overs (7-15): India 7.2 vs Australia 7.5 — Both largely rely on spinners here, but India's part-time options are weaker.
Death (16-20): India 8.8 vs Australia 9.1 — Bumrah's yorker prowess (8.2 death econ) is the differentiator. Without him, India's death bowling average balloons to 9.6.
India's entire pace advantage rests on one man. Remove Bumrah from the stats and India's overall pace economy rises to 8.3 — worse than Australia's 7.8. This single-player dependency is India's greatest tactical vulnerability going into the 2026 England tour.
✦ India's homegrown AI models now lead global Indic-language benchmarks — outperforming Silicon Valley across all 22 scheduled languages.
| # | Model | Org | Indic | Global | ||
|---|---|---|---|---|---|---|
| # | Model | Org | Indic | Global | ||
| 1 | Sarvam-105B | Sarvam AI | 🇮🇳 | 90% | 18% | MADE IN INDIA |
| 2 | Sarvam-30B | Sarvam AI | 🇮🇳 | 89% | 16% | MADE IN INDIA |
| 3 | IndicTrans2 / Airavata | AI4Bharat (IIT Madras) | 🇮🇳 | 76% | 10% | MADE IN INDIA |
| 4 | BharatGen Param2-17B | BharatGen (IIT Bombay) | 🇮🇳 | 72% | 12% | MADE IN INDIA |
| 5 | Hanooman (up to 40B) | SML x BharatGPT | 🇮🇳 | 68% | 11% | MADE IN INDIA |
| 6 | Gnani.ai Voice LLM | Gnani.ai | 🇮🇳 | 63% | 9% | MADE IN INDIA |
| 7 | Krutrim-3 | Ola Krutrim | 🇮🇳 | 60% | 8% | MADE IN INDIA |
| 8 | Project Indus (8B) | Tech Mahindra | 🇮🇳 | 58% | 9% | MADE IN INDIA |
Sources: LMArena / Chatbot Arena Elo, Stanford HAI, Open LLM Leaderboard, HuggingFace, AI4Bharat. Last evaluated: July 11, 2026.
| # | Title | Album/Label | Streams | Trend |
|---|---|---|---|---|
| 1 | Raanjhan (Sachet-Parampara) | Do Patti | 246M+ streams | HOT |
| 2 | Finding Her (Kushagra) | Independent (I-Pop) | Top 5 India | HOT |
| 3 | Heeriye (Arijit Singh & Jasleen Royal) | Single | Top 5 India | HOT |
| 4 | Tauba Tauba (Karan Aujla) | Bad Newz | Top 10 India | HOT |
| 5 | Softly (Karan Aujla) | Independent (P-Pop) | Top 10 India | UP |
| 6 | Saiyaara Title Track (Arijit Singh) | Saiyaara OST | Top 10 India | UP |
| 7 | Chaleya (Arijit Singh & Shilpa Rao) | Jawan Legacy | 200M+ streams | UP |
| 8 | Bhediya Title Track (Sachin-Jigar) | Bhediya 2 OST | Top 10 India | UP |
| 9 | Anuv Jain breakout (Husn) | Independent (I-Pop) | Top 10 India | HOT |
| 10 | Ghar Kab Aaoge (Arijit Singh) | Border 2 OST | Trending 2026 | NEW |
| # | Title | Lead | Buzz Score | Trend |
|---|---|---|---|---|
| 1 | Dhurandhar | Ranveer Singh | ₹853Cr WW — All-Time Blockbuster | HOT |
| 2 | Chhaava | Vicky Kaushal | ₹797Cr WW — Blockbuster | HOT |
| 3 | Saiyaara | Ensemble Cast | ₹579Cr WW — Blockbuster | HOT |
| 4 | Border 2 | Sunny Deol | ₹485Cr WW — Final (2026) | HOT |
| 5 | War 2 | Hrithik Roshan, Jr NTR | ₹303Cr WW — Hit | UP |
| 6 | Mardaani 3 | Rani Mukerji | ₹75Cr WW — Final (2026) | NEW |
| 7 | O Romeo | Shahid Kapoor | ₹132Cr WW — Final (2026) | NEW |
| 8 | Ikkis | Dhawan / Kapoor | ₹41.65Cr WW (2026) | NEW |
| 9 | Sitaare Zameen Par | Aamir Khan | Released Mar 2026 | NEW |
| 10 | Thamma | Ensemble Cast | 2025 — Hit | UP |
| # | Title | Platform | Rating | Trend |
|---|---|---|---|---|
| 1 | Panchayat S4 | Prime Video | IMDb: 9.0 (115K+ votes) | HOT |
| 2 | The Family Man S3 | Prime Video | IMDb: 8.7 (110K+ votes) | HOT |
| 3 | Mirzapur S3 | Prime Video | IMDb: 8.4 (90K+ votes) | HOT |
| 4 | Paatal Lok S2 | Prime Video | IMDb: 8.3 (50K+ votes) | HOT |
| 5 | Black Warrant | Netflix | IMDb: 7.9 (7.8K+ votes) | NEW |
| 6 | The Bads of Bollywood | Netflix (Aryan Khan) | IMDb Most Popular #1 | NEW |
| 7 | Khauf | JioCinema | IMDb: 7.5 | UP |
| 8 | Khakee: Bengal Chapter | Netflix | IMDb: 7.5 | UP |
| 9 | Dupahiya | JioCinema | IMDb: 7.4 | UP |
| 10 | Criminal Justice: A Family Matter | Hotstar (Pankaj Tripathi) | IMDb: 7.2 | UP |
| # | Title | Host | Listeners | Trend |
|---|---|---|---|---|
| 1 | The Ranveer Show | Ranveer Allahbadia | Top India Charts | HOT |
| 2 | Figuring Out | Raj Shamani | Top India Charts | HOT |
| 3 | Beer Biceps | Ranveer Allahbadia | Top India Charts | UP |
| 4 | Dostcast | Kusha Kapila & Simone | Trending | UP |
| 5 | The Kapil Sharma Show Podcast | Kapil Sharma | Trending | UP |
| 6 | Cyrus Says | Cyrus Broacha | Trending | UP |
| 7 | On Purpose (India Edition) | Jay Shetty | Top Global Charts | UP |
| 8 | Barbershop with Shantanu | Shantanu Deshpande | Trending | UP |
| 9 | Hindi Kavita | Various Poets | Trending | UP |
| 10 | The Musafir Stories | Saif Omar | Trending | UP |
| # | Title | Platform | Rating | Trend |
|---|---|---|---|---|
| 1 | Panchayat S4 | Prime Video | IMDb: 8.0 | HOT |
| 2 | Aspirants S2 | TVF/Prime Video | Trending | UP |
| 3 | Gullak S5 | SonyLIV | Trending | UP |
| 4 | Kota Factory S3 | Netflix | Trending | UP |
| 5 | The Family Man S3 | Prime Video | IMDb: 8.7 (series) | HOT |
| 6 | Scam 2026 | SonyLIV | Announced | NEW |
| 7 | Rocket Boys S3 | SonyLIV | Announced | NEW |
| 8 | Mirzapur S3 | Prime Video | Trending | UP |
| 9 | Made in Heaven S3 | Prime Video | Announced | NEW |
| 10 | Kohrra S2 | Netflix | Announced | NEW |
⚠ Disclaimer: Investment figures are based on public company announcements and news reports as of February 2026. These amounts are for informational purposes only and should not be relied upon for investment decisions. Figures may be incomplete, superseded, or subject to change. This is NOT investment advice.
| Company | Investment (INR / USD) | Sector | Timeline | Status | Source |
|---|---|---|---|---|---|
| Amazon | ₹2,90,500 Cr (reported) ($35B) | Cloud + AI Infra | 2025-30 | Committed | Amazon Press Release / ET Tech |
| Infosys | ₹16,600 Cr (reported) ($2B) | Enterprise AI Services (client deployments) | 2025-26 | Active | Infosys Annual Report (AI services revenue, not capital investment) |
| Microsoft | ₹1,45,250 Cr (reported) ($17.5B) | Azure AI + Data Centers | 2025-28 | Committed | Microsoft Blog / Reuters |
| ₹1,24,500 Cr (reported) ($15B) | AI Research + Cloud Infra | 2026-30 | Committed | Google India Blog / Reuters Feb 2026 | |
| Reliance Industries | ₹9,13,000 Cr (reported) ($110B (7-year)) | AI Infrastructure + Data Centers | 2026-33 | Committed | TechCrunch Feb 2026 / India AI Summit |
| Neysa (GenAI Infra) | ₹9,960 Cr (reported) ($1.2B) | GenAI Infrastructure | 2026 | Active | Inc42 / Crunchbase (Blackstone-led, Feb 2026) |
| Nvidia | ₹8,300 Cr+ ($1B+) | GPU Supply | 2025-26 | Building | ET Tech |
| Wipro | ₹8,300 Cr (reported) ($1B) | AI Services | 2025 | Active | Wipro Q3 Report |
| Govt of India | ₹10,372 Cr (reported) ($1.25B) | IndiaAI Mission | 2024-29 | Active | PIB PRID 2225781 / MeitY |
| Tata Group | ₹4,150 Cr (reported) ($500M) | AI Semiconductor | 2026 | Planned | ET Tech |
| Adani Group | ₹8,30,000 Cr (reported) ($100B (planned)) | AI Data Centers | 2026-35 | Planned | India AI Summit Feb 2026 / Bloomberg |
| Yotta Data Services | ₹16,600 Cr (reported) ($2B) | AI Hub + Nvidia GPUs | 2026-28 | Building | CNBC Feb 2026 |
| Sarvam AI | ₹341 Cr (reported) ($41M Series A (total $53.8M)) | Sovereign LLM | 2023 | Active | Crunchbase |
Sources: Company press releases, ET Tech, VCCircle, NASSCOM, MeitY.
| Metric | 🇮🇳 India | 🇨🇳 China | 🇺🇸 USA | 🇪🇺 EU | India Trend |
|---|---|---|---|---|---|
| AI Startups | 3,000+ | 15,000+ | 18,000+ | 8,000+ | ↑ 35% YoY |
| 💡 India's AI startup ecosystem is rapidly scaling. With 3,000+ AI startups registered with NASSCOM, India trails China and USA but leads emerging economies. Growth driven by deeptech funding and government recognition (DPIIT, MeitY support). | |||||
| AI Funding 2025 | $4.2B | $38B | $110B+ | $18B | ↑ Strong |
| 💡 India's $4.2B AI funding (NASSCOM/VCCircle aggregate across AI, deeptech, and GenAI startups) reflects rising investor confidence. USA leads with $110B+ (Stanford AI Index 2025). | |||||
| AI Talent Pool | 1.2M+ | 2.5M | 3.2M | 2.1M | ↑ 28% growth |
| 💡 India has 1.2M+ AI/ML trained professionals (NASSCOM-2025 survey). IIT-IISc-IIIT ecosystem produces 40K+ AI-capable engineers annually. Global talent arbitrage benefits Indian startups and MNCs. | |||||
| Research Papers 2024 | 22,000+ | 98,000+ | 75,000+ | 65,000+ | ↑ 22% YoY |
| 💡 Indian researchers published 22,000+ peer-reviewed papers in AI/ML (arxiv.org, Google Scholar analysis 2024). IIT, IISc, and IIIT institutions lead. China dominates volume; USA leads citations (Stanford AI Index 2025). | |||||
| AI Patents Filed | 16,000+ | 120,000+ | 85,000+ | 15,000 | ↑ 40% YoY |
| 💡 India filed 16,000+ AI patents in 2024 (WIPO World IP Indicators 2025, cumulative filings accelerating). Increased corporate R&D (TCS, Infosys, Flipkart) and deeptech support driving growth. | |||||
| Government AI Budget | $1.3B | $15B+ | $3.3B | $4.5B | ↑ $1.3B allocated |
| 💡 India's AI policy budget (MeitY, NITI Aayog, DSIR) totals $1.3B for 2025-2026. Budget 2026 allocates ₹40,000Cr for electronics manufacturing (includes AI chips). China's $15B+ reflects massive deeptech bet. | |||||
| AI Adoption Rate | 72% | 58% | 65% | 55% | ↑ Highest globally |
| 💡 72% of Indian enterprises are actively piloting/deploying AI solutions (NASSCOM-McKinsey 2025 study). Enterprise GenAI adoption at 73% (NASSCOM-McKinsey 2025 — enterprise-level metric, distinct from BCG employee-level 92%). Higher than China, USA, EU due to leapfrogging in fintech/agritech. | |||||
| Compute Capacity | Growing/Tier 2 | #2 Global | #1 Global | #4 Global | ↑ Strategic build |
| 💡 India's compute infrastructure is rapidly developing. Budget 2026 20-year tax holiday for data centers attracts global players (Google, Microsoft, Amazon building regional hubs). Jio-Meta partnership expanding edge compute across India. | |||||
Sources: NSE India, BSE India, Moneycontrol, RBI bulletins, SEBI filings. Analysis based on public data through Feb 2026.
| # | Role | Avg CTC | Range | Demand | Openings | Growth | Top Hiring | Key Skills |
|---|---|---|---|---|---|---|---|---|
| 1 | ML Engineer | ₹14L | ₹10-24L | ▲ High | High | High | Google, Microsoft, Flipkart | Python, PyTorch, MLOps |
| 2 | Data Scientist | ₹13L | ₹9-20L | ▲ High | High | High | Amazon, Flipkart, Paytm | Statistics, SQL, Tableau |
| 3 | GenAI Developer | ₹12L | ₹6-22L | ▲ Very High | High | High | Sarvam AI, Observ.AI, Fractal AI | LLM APIs, Prompt Engineering, FastAPI |
| 4 | NLP Engineer | ₹25L | ₹13-50L | ▲ High | Moderate | High | Google, Microsoft, Sarvam | Transformers, Indic NLP, BERT |
| 5 | Computer Vision Engineer | ₹23L | ₹12-46L | ▲ High | Moderate | High | Microsoft, Amazon, Nvidia | OpenCV, YOLO, CNN Architectures |
| 6 | MLOps Engineer | ₹27L | ₹15-54L | ▲ High | Moderate | High | Flipkart, Amazon, Swiggy | Kubernetes, Docker, Airflow |
| 7 | AI Product Manager | ₹28L | ₹16-56L | ▲ High | Moderate | High | Google, Microsoft, PhonePe | AI Strategy, Analytics, Communication |
| 8 | Prompt Engineer | ₹6L | ₹4-10L | ▲ High | Growing | Emerging | Sarvam AI, Yellow.ai, Fractal AI | LLM Interaction, Domain Expertise |
| 9 | AI Research Scientist | ₹26L | ₹14-52L | ▲ Moderate | Limited | Medium | IIT Bombay (CSRI), Microsoft, Google | Research Publications, Paper Writing |
| 10 | Robotics AI Engineer | ₹24L | ₹12-48L | ▲ High | Niche | Emerging | IIT Madras, Mercedes, Siemens | ROS, Kinematics, Control Systems |
| 11 | LLM Fine-tuning Specialist | ₹25L | ₹13-50L | ▲ Very High | Growing | Emerging | Sarvam AI, TCS, Fractal AI | LoRA, QLoRA, Custom Datasets |
| 12 | AI Ethics Researcher | ₹22L | ₹12-44L | ▲ High | Niche | Medium | IISc, Google, Microsoft | Policy, Fairness, Bias Analysis |
| 13 | AI Solutions Architect | ₹25L | ₹18-35L | ▲ High | Moderate | High | IBM, Accenture, HCL | Enterprise Architecture, AI Design |
| 14 | Deep Learning Engineer | ₹25L | ₹13-50L | ▲ High | Moderate | High | Google, Microsoft, Nvidia | TensorFlow, Keras, Model Optimization |
| 15 | AI Infrastructure Engineer | ₹28L | ₹15-56L | ▲ High | Moderate | High | Amazon, Flipkart, Nvidia | GPU Clusters, CUDA, Distributed Training |
There are 1.44 billion people on this subcontinent. Sixty percent of them are under 35. The country that built UPI, Aadhaar, and the world's largest biometric identity system in a single decade is now building sovereign AI — and the velocity is staggering. $67.5 billion committed. 92% GenAI adoption (BCG ‘AI at Work’ 2025) — highest of any major economy. Three of the world's ten most-funded AI labs now have India engineering centers. The question is no longer whether India will matter in AI. The question is how India will shape the global AI landscape going forward.
We are 1.44 billion stories waiting to be told. The youngest major workforce on Earth (median age 28.4, CIA World Factbook). The fastest-growing large economy. The architects of UPI, Aadhaar, and one of the most advanced digital public infrastructure stacks any democracy has built (IMF 2023). And now, we are building sovereign AI — in our languages, for our people, on our terms.
bharath.ai is the chronicle of this revolution. We track the models, the money, the policy, the breakthroughs, the cricket analytics, the cinema predictions, the state-by-state workforce data — everything that makes India's AI story the most exciting story on Earth. Every source linked. Every prediction grounded in publicly verifiable data. All analysis is grounded in publicly verifiable sources.
Our India AI State Map — tracking every state's AI ecosystem from Bangalore to Bhubaneswar — and Regional Language AI Status tracker are the pulse of India's forward momentum. From 22 scheduled languages gaining AI readiness to state-level policy scores, investment pipelines, and talent concentration maps, these sections capture the India Pulse: a real-time portrait of a nation accelerating into the future. This is not retrospective reporting — this is forward-facing intelligence.
We don't just report the future. We believe in it. We believe that when one of the world's most resourceful populations embraces AI technology, the results are transformative — for India and for the world.
Whether you're a founder in Bangalore, a student in Jaipur, a policymaker in Delhi, or a mother in Varanasi whose child just asked their first question to an AI — in Hindi — this publication is for you. This is your story. We're just making sure the world hears it.
Transparency: the bharath.ai data desk uses statistical models under editorial review to synthesize, rank, and forecast from verified public data. Every prediction and projection is backed by cited sources and auditable methodology. We are an independent AI-powered news and analysis platform. Readers can verify every claim through the source links provided in each article.
bharath.ai is refreshed on a daily to weekly basis. Content is continuously updated through AI-powered analysis pipelines with human oversight.
For inquiries, partnerships, or corrections. We welcome tips from researchers, founders, and policymakers.
India's AI pulse, every Monday morning. Free forever.