TL;DR

Blackstone-backed AirTrunk plans to invest $30 billion in India by 2030, building 5GW of data centre capacity across multiple states. The announcement comes six weeks after AirTrunk entered India through its acquisition of Lumina CloudInfra.

Six weeks ago, AirTrunk did not operate in India. Now it wants to spend $30 billion there.

The Blackstone-backed hyperscale data centre operator announced on Thursday that it plans to invest more than INR 3,000 billion ($30 billion) in India by 2030, building over 5 gigawatts of digital infrastructure capacity across multiple states and union territories. The figure represents planned spending, not committed capital, and the four-year timeline leaves considerable room for adjustment. Still, if executed, the programme would rank among the largest digital infrastructure commitments in the country’s history.

Prime Minister Narendra Modi publicly welcomed the commitment, saying it would strengthen India’s position as a global hub for cloud computing and AI. The endorsement followed meetings between AirTrunk founder and CEO Robin Khuda and federal and state government officials in Maharashtra and Andhra Pradesh.

From zero to $30 billion in six weeks

AirTrunk entered India in April through the acquisition of Lumina CloudInfra, which gave it a 600-megawatt development pipeline across Mumbai, Chennai, and Hyderabad. The new $30 billion plan represents a dramatic escalation of that position.

The centrepiece is a 3GW campus at the Raigad Penn Growth Centre on the outskirts of Mumbai, for which AirTrunk has signed a letter of intent for land allotment with the Maharashtra government. According to a single industry report, that project alone carries an estimated price tag of $21 billion, though the figure has not been confirmed by AirTrunk or the Maharashtra government.

“Capital is mobile, and India is creating the conditions for it to thrive,” Khuda said. “India is taking a top-down approach to AI with clear government-led initiatives, a world-class talent pool, and massive availability of renewable energy.”

Why India, why now

India’s data centre market has been accelerating since 2024, but the pace of new commitments in 2026 has been extraordinary. Google has pledged $15 billion for a southern Indian data centre hub. Microsoft has committed $17.5 billion. Amazon is targeting up to $35 billion by 2030. The Adani Group has reportedly outlined a $100 billion programme through 2035, including a 5GW renewable-powered hyperscale platform, though those figures come from industry reports rather than a formal company commitment.

The government has matched the private capital with policy. India’s February budget introduced a 20-year tax holiday through 2047 for foreign technology firms using Indian data centres for global cloud services. The IndiaAI Mission has received approximately £1 billion ($1.2 billion) in funding, and the India Semiconductor Mission has been backed with approximately £7.5 billion ($9 billion).

AI-related colocation leasing more than doubled to 348MW in the past year, now accounting for nearly 20% of total demand. Between March 2025 and April 2026, operators announced roughly 30 large projects adding about 3.5GW of planned capacity across the country. Schneider Electric expects its India data centre business to become its single largest unit within three to five years.

Blackstone’s hyperscale bet

AirTrunk is the vehicle through which Blackstone is making its largest infrastructure play in the Asia-Pacific region. The private equity giant acquired AirTrunk in December 2024 for an implied enterprise value of over A$24 billion ($16 billion), alongside Canada Pension Plan Investment Board, which took a 12% stake. It was the largest data centre transaction in history at the time.

Blackstone has since been expanding AirTrunk’s footprint aggressively. The platform now spans more than 3GW of operating and planned capacity across 20 campuses in six regions: Australia, Singapore, Japan, Malaysia, Hong Kong, and India. Separately, Blackstone is seeking up to $1.75 billion in a NYSE IPO for its Digital Infrastructure Trust, packaging hyperscaler-leased AI data centres as a public REIT.

The India push fits a clear pattern. Blackstone had already committed approximately $11 billion to Indian data centres through Lumina before the AirTrunk acquisition. The new $30 billion figure nearly triples that exposure.

The execution question

The numbers are staggering, but so is the gap between announcements and operational capacity. India’s total live IT capacity exceeded 1.6GW by the end of 2025, the product of years of cumulative buildout. Just 371MW was added in 2025 alone. AirTrunk’s proposed 5GW, combined with the commitments from Google, Microsoft, Amazon, and Adani, would require India to build more capacity in the next four years than it has built in its entire history, several times over.

The discussions between Khuda and government officials reportedly focused on precisely the bottlenecks that could slow that buildout: access to reliable and cost-effective power, renewable energy, sustainable water supply, talent development, streamlined approvals, and coordination between state and federal governments on strategic infrastructure.

India is not the only country chasing hyperscale AI infrastructure investment. Malaysia, Saudi Arabia, and several European nations are offering competing incentive packages. AirTrunk itself recently expanded its Malaysian platform to over 700MW. The $30 billion figure signals intent, but the timeline to 2030 leaves room for the kind of recalibration that large infrastructure programmes routinely undergo.

What is not in question is the direction of travel. Whether the final number is $30 billion or something smaller, India is rapidly becoming one of the world’s primary construction sites for the physical infrastructure that AI requires. The question is whether the country’s grid, water supply, and planning systems can keep pace with the capital flooding in.

The Huntington Beach defence-tech startup, run by a 22-year-old MIT dropout, has raised a $300M Series C at a $1.8bn valuation, nearly 4x its mark from June 2025.

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Mach Industries, the three-year-old defence-tech startup run by 22-year-old founder and chief executive Ethan Thornton, has raised a $300m Series C at a $1.8bn valuation, nearly four times the $470m valuation it hit when Sequoia and Khosla Ventures led its $100m round in June 2025.

The round was co-led by Ribbit Capital and the deep-tech-focused Infinite Capital, with Bedrock, Sequoia and Khosla following on. The funding lands inside what is now an unmistakable Pentagon push toward what defence officials are calling “drone dominance”.

The Mach trajectory is itself worth pausing on. Thornton dropped out of MIT in 2023 to start Mach as a teenager; the company has grown from roughly a dozen employees in its first year to about 350 today. Its core production facility sits in Huntington Beach, California, with a 115,000-square-foot manufacturing footprint and additional design-and-production locations elsewhere.

The product roadmap now spans five autonomous vehicles in development: Viper, a jet-powered vertical-takeoff vehicle; Glide, a high-altitude glider capable of launching weapons; Stratos, an airborne surveillance platform; Dart, a low-cost counter-drone interceptor; and Pike, a long-range munition-launch platform. The five-vehicle catalogue is unusually broad for a company at Mach’s stage.

The Pentagon-side context is the part that explains how a 22-year-old’s defence startup gets to $1.8bn in three years. The current US defence-procurement environment has shifted decisively toward cheap, attritable, AI-enabled drone systems over the past 18 months, on the explicit theory that future conflicts will be won by whichever side can produce more drones per dollar.

Mach’s low-cost Dart interceptor and Pike launch platform sit cleanly inside that procurement preference. Ukraine’s drone-war evidence and the Iran-Israel conflict of 2025 have, between them, produced the political case for sustained investment in the category at scale.

The valuation pop, in that frame, is not really about Mach as a company. It is about the size of the addressable market the Pentagon has now publicly committed to. Anduril hit $61bn earlier this year after winning a Pentagon enterprise agreement worth up to $20bn over 10 years. Shield AI reached $12.7bn on its autonomous-combat-pilot Hivemind business.

Berlin’s Stark is raising at €2.5bn, 18 months after founding. Helsing is now one of Europe’s five most valuable private tech firms. Defence-tech VC hit a record $49bn globally in 2025, roughly double the prior year. Mach’s $1.8bn is, against that backdrop, a relatively conservative re-rating rather than an aggressive one.

What is unusual about Mach specifically is the speed of operational scaling. Most defence-tech startups at $1.8bn valuations have either a single deeply specialised product (Hivemind for Shield AI, Lattice for Anduril, the SG-1 Fathom autonomous mini-submarine for Helsing) or a deep-government-customer programme that produces predictable revenue.

Mach is attempting five products simultaneously while still pre-revenue at scale. That is a meaningfully different risk profile from the established defence-tech unicorns; investors are betting Thornton can execute Anduril-scale manufacturing inside three years of company existence.

The cap-table composition is telling. Ribbit Capital, the fintech-and-crypto-anchored fund best known for backing Robinhood and Nubank, has been increasingly visible in deep-tech and AI-infrastructure deals over the past year, including Cognition and Crusoe. Infinite Capital is the explicit deep-tech vehicle in the round.

The pairing signals that Mach is being underwritten partly as a manufacturing-scale-up bet (Infinite Capital’s lane) and partly as a category-defining brand bet (Ribbit’s consumer-and-narrative lane). Both reads sit inside Thornton’s public framing of Mach as a generational US defence-manufacturing company rather than a single-product vendor.

The risk profile is, accordingly, asymmetric. If the five-vehicle roadmap delivers and Pentagon procurement commits at production scale, Mach plausibly reaches the multi-billion-dollar revenue tier the current valuation implies. If even two of the five vehicles fail to reach contracted production, the $1.8bn is exposed to substantial compression. The next 24 months of Pentagon contract-award disclosures will indicate which way the bet pays off.

Mach has not disclosed revenue figures or specific government contract values.

The ride-hailing company is betting that Germany’s automotive heartland, and a less sensor-heavy approach to autonomy, can finally make robotaxis scale in Europe.

Munich is about to become a test of a particular theory: that the cheapest way to put a driverless taxi on a European street is to stop building special cars for it. Uber said on Sunday that it will launch a robotaxi programme in the German city alongside Autobrains, an Israeli autonomy firm, with the vehicles running on Nvidia’s DRIVE Hyperion platform.

The announcement was made at Nvidia’s GTC conference in Taipei, and the deployment is contingent on German regulatory approval.

The choice of city is not incidental. Munich is the home of BMW and a dense cluster of suppliers, and it offers the mix Uber says it wants: tight inner-city streets, fast ring roads, and what the company politely calls “a thoughtful German regulatory framework.”

Germany has had federal rules permitting driverless vehicles in defined operating areas since 2021, which makes it one of the few European markets where a Level 4 service is a paperwork problem rather than a legal impossibility.

What is genuinely different here is the autonomy stack. Most robotaxis on the road today, the ones run by Waymo and its peers, depend on bespoke vehicles bristling with lidar and a single large end-to-end model trained to do everything at once.

Autobrains is selling the opposite. Its “agentic AI” breaks the driving task into specialised agents, each handling a slice of the problem, running on standard automotive sensors and ordinary automotive-grade compute. The pitch is that this is cheaper to build and easier to drop into any carmaker’s vehicle.

That last point is the commercial idea Uber keeps returning to. The three companies describe the programme as “OEM-agnostic,” meaning the software is meant to run across different manufacturers’ cars rather than a single custom fleet.

“Autonomous driving will not scale by relying on a single model to solve every driving scenario,” said Igal Raichelgauz, Autobrains’ chief executive and founder. “It requires systems that can reason, adapt, and make decisions under uncertainty.”

Uber, which sold its own self-driving unit in 2020, has spent the years since assembling exactly this kind of partnership rather than owning the technology.

It is the same template behind its Tokyo pilot with Wayve and Nissan and its tie-up with Pony.ai and Verne, whose vehicles became Europe’s first commercial robotaxi service in Zagreb earlier this year. Sarfraz Maredia, Uber’s global head of autonomous mobility, framed Munich in the same terms: the hard part, he said, “is bringing them into a commercial network where they can reliably serve riders at scale.”

Several things were left unsaid. The companies named no launch date, no fleet size, and no vehicle. They did not say which carmaker, if any, would supply the cars, nor whether early rides would carry safety operators, as they do in Zagreb.

The Munich plan also tracks a target Uber flagged last year, when it first signalled an intention to begin self-driving operations in the city, so the announcement firms up a timeline more than it sets a new one.

Europe has been the continent where robotaxis are announced more often than they are ridden. Munich is now on the list of places where that is supposed to change, pending a regulator’s signature.