Quantum Space, a startup with plans to build highly maneuverable spacecraft for the U.S. military, announced plans to go public through a $1.2 billion merger with a publicly traded special purpose acquisition company, or SPAC.

In a season of mega-IPOs, there’s something almost quaint about a SPAC — in 2021, a fad for going public through the vehicle began in the space sector and spread throughout the tech world. Many SPACs proved disastrous for retail investors who wagered on immature companies, but a few deals, notably Rocket Lab and Planet, proved successful.

Another positive outcome was Intuitive Machines, a purpose-built NASA contractor launched by Kam Ghaffarian, a long-time space investor who backed a team of former NASA officials eager to sell their expertise back to the agency. Today, Intuitive Machines is a $6.4 billion company sending a regular cadence of robotic missions to the moon.

Now, Ghaffarian is trying to do it again with Quantum Space, a startup he launched in 2020 to capitalize on the founding of the U.S. Space Force and the growing need for vehicles that can move between orbits and rendezvous with other spacecraft.

“Defense spending, space infrastructure, and America’s strategic priorities in orbit are converging at exactly the moment Quantum Space is ready to scale,” Ghaffarian told TechCrunch. “The Space Force’s requirements are growing rapidly, and demand for maneuverable spacecraft is accelerating. Ranger is purpose-built to meet both.”

At the helm is CEO Jim Bridenstine, a former member of Congress and the NASA administrator during President Donald Trump’s first term. A champion of public-private partnerships, Bridenstine will aim to leverage his knowledge of the space industry to win key contracts.

Quantum Space is involved in six government development programs, including one that may see its vehicle head for the moon. But the company has a simple focus.

“We are designed specifically for the national security,” Bridenstine said. While most satellites only carry enough fuel to alter their position slightly and eventually dispose of themselves, a newer generation of spacecraft — including some fielded by Russia and China — are designed to move rapidly between orbits and remain in place for sustained surveillance work.

Ranger, the company’s spacecraft, is designed to match and exceed those competitors. It is expected to carry significant fuel, allowing it to remain in high orbits over long periods to watch rival satellites. The vehicle also has to be refuellable in order to qualify for Andromeda task orders.

Quantum Space was selected to join the Andromeda contract, a $6.2 billion effort that will task companies to develop vehicles for space-based reconnaissance. Now it has to win task orders for actual funded missions starting in 2030.

The SPAC transaction is expected to raise $300 million in private investment alongside any public proceeds, which will be used to build manufacturing facilities in Tulsa, Oklahoma, capable of producing one Ranger per quarter by the end of 2028. The next step is launching the first Ranger prototype to orbit in 2027. The deal is sponsored by Mike Blitzer, the financier who helped bring Intuitive Machines and USA Rare Earth to public markets.

Still, the decision to leave private markets behind highlights the competition Quantum Space faces. True Anomaly, a startup that is also competing for Andromeda task orders, has raised $1 billion from venture investors. The company is also looking to beat out established defense contractors like Lockheed Martin, Northrop Grumman, and Boeing’s Millennium Space Systems, among others.

TL;DR

Microsoft unveiled Majorana 2, a quantum chip with qubits 1,000x more reliable than its predecessor, achieving a mean 20-second lifetime versus microseconds for competitors. Agentic AI via Microsoft Discovery accelerated the development, and Microsoft now targets a scalable quantum computer by 2029, halving its original timeline.

Microsoft has unveiled Majorana 2, a next-generation topological quantum chip whose qubits are 1,000 times more reliable than those in the first Majorana chip introduced last year. The improvement is so significant that Microsoft has cut its timeline for achieving a scalable quantum computer from 2033 to 2029, halving the original target. The company credits agentic AI, deployed through its Microsoft Discovery research platform, with accelerating the materials science, fabrication optimisation, and measurement automation that made the leap possible.

The numbers are striking. Majorana 2’s qubits maintain their quantum state for a mean lifetime of 20 seconds, with some instances lasting as long as one minute. Most competing quantum approaches measure qubit lifetimes in microseconds. Microsoft’s analogy: it is roughly comparable to a phone battery that lasts three years on a single charge instead of dying in a day. Combined with one-microsecond operations and a qubit size of 1/100th of a millimetre, the chip puts Microsoft on what it describes as a path to commercially valuable quantum computing by the end of the decade.

How agentic AI built a better chip

The key materials change was switching from aluminium to lead as the superconductor. Lead naturally shields qubits from cosmic disturbances that cause instability, but working with it introduced tradeoffs that took years to overcome. Quantum computing startups across Europe and the US are pursuing different approaches to the qubit stability problem, but Microsoft’s topological approach, which creates an entirely new state of matter, is architecturally distinct from the superconducting circuits used by IBM, Google, and most competitors.

Microsoft Discovery’s AI agents were deployed across the quantum team’s workflow in several ways. Agents automated the measurement process that previously took weeks when done manually, cutting cycle time by orders of magnitude. They analysed nearly two decades of experimental data across multiple formats and silos, finding correlations that no individual researcher could see across that volume. They optimised fabrication processes by running simulations to identify the most promising material compositions before physical experimentation. And they detected an uncalibrated temperature sensor that was introducing noise into the fabrication process, a flaw that had gone unnoticed by human review.

“Agentic AI has permeated almost everything we do,” said Chetan Nayak, Microsoft technical fellow. The application of AI to quantum hardware development represents a convergence that could accelerate the entire field: better AI helps build better quantum computers, which in turn could eventually run better AI.

Microsoft Discovery goes public

Alongside the Majorana 2 announcement, Microsoft made its Discovery platform generally available. The platform lets organisations deploy autonomous AI agent teams, guided by human expertise, to speed scientific research and development. It includes a Discovery Engine for research and reasoning workflows, enterprise-grade security and governance, and integration with Azure. Google, Anthropic, and OpenAI are all pursuing AI for science, but Microsoft is the first to ship a commercially available platform specifically designed for frontier R&D with built-in agent orchestration.

Microsoft also introduced a free Discovery app in early preview that individuals can download and run locally with a GitHub Copilot account. Customers including chemical company Syensqo are already using the platform to develop next-generation fluids for semiconductor manufacturing.

The competitive context

The quantum computing sector is experiencing a funding and IPO boom. Quantinuum’s massively oversubscribed IPO this week valued the Honeywell-backed company at $14.3 billion. The US government committed $2 billion to quantum firms in May, with IBM receiving $1 billion for its Anderon quantum chip foundry. Focused Energy raised $240 million for laser fusion. The market is pricing in the expectation that quantum will follow AI’s trajectory from laboratory curiosity to commercial capability within this decade.

Microsoft’s topological approach has been the most controversial in the field. The company’s 2018 claim to have observed Majorana zero modes was retracted after independent scrutiny. Majorana 1, introduced in 2025, re-established credibility with peer-reviewed results. Majorana 2’s 1,000x improvement and the accelerated 2029 timeline will face similar scrutiny, and the peer-reviewed paper accompanying the announcement will be the definitive test of whether the results hold up.

The energy and compute demands of AI make quantum computing’s potential more commercially relevant than at any point in its history. If Microsoft can deliver a scalable topological quantum computer by 2029, the applications in drug discovery, materials science, cryptography, and optimisation would be transformative. If it cannot, the 2029 target will join a long list of quantum computing timelines that proved optimistic. The difference this time is that AI is accelerating the research itself.