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Space startup achieves unicorn status with orbital computing vision

Starcloud raises $170 million Series A to build data centers in space

Starcloud has secured $170 million in Series A funding, valuing the space computing company at $1.1 billion and making it one of the fastest Y Combinator graduates to reach unicorn status. The round, led by Benchmark and EQT Ventures just 17 months after demo day, signals growing investor interest in orbital data centers as terrestrial development faces resource and regulatory challenges.

With total funding now at $200 million, Starcloud launched its first satellite featuring an Nvidia H100 GPU in November 2025. The company plans to deploy Starcloud 2 later this year, equipped with multiple GPUs including Nvidia's Blackwell chip, AWS server blade, and bitcoin mining hardware.

The ambitious roadmap includes Starcloud 3, a 200-kilowatt spacecraft designed to launch aboard SpaceX's Starship rocket. This three-ton data center will utilize SpaceX's "PEZ dispenser" deployment system originally created for Starlink satellites. CEO Philip Johnston expects this to be the first orbital data center competitive with Earth-based facilities, targeting $.05 per kw/hour power costs if launch expenses reach $500 per kilogram.

However, the business model faces significant hurdles. Starship hasn't achieved commercial operations yet, with Johnston anticipating availability between 2028-2029. Without low-cost heavy-lift capabilities, space data centers remain economically unviable compared to terrestrial alternatives.

"If it ends up being delayed, we'll just carry on launching the smaller versions on Falcon 9," Johnston said. "We're not going to be competitive on energy costs until Starship is flying frequently."

Starcloud operates on two business models: selling processing power to other spacecraft (their first satellite analyzes Capella Space radar data) and eventually competing with terrestrial data centers when launch costs decrease. The company claims several firsts, including training an AI model in orbit and running Google's Gemini in space.

The technical challenges are immense. Space-based GPUs number in the dozens while Nvidia sold nearly 4 million to terrestrial customers in 2025. SpaceX's 10,000-satellite Starlink network generates around 200 megawatts, compared to U.S. data centers under construction exceeding 25 gigawatts.

Johnston acknowledges the H100 isn't optimal for space conditions – another GPU failed during launch – but the experience provides crucial insights for future designs. Starcloud-2 will feature the largest deployable radiator on a private satellite to address cooling challenges.

Synchronization presents another obstacle. Large-scale AI training requires hundreds of GPUs working simultaneously, necessitating either massive spacecraft or reliable inter-satellite laser communications. Most industry experts expect simple inference tasks to precede complex training workloads in space.

Competition is intensifying with Aetherflux, Google's Project Suncatcher, and Aethero all developing space computing solutions. Aethero launched Nvidia's first space-based Jetson GPU in 2025. The biggest threat may be SpaceX itself, which has requested permission for a million-satellite distributed computing constellation.

Despite the formidable competition, Johnston sees opportunity for coexistence. "They are building for a slightly different use case than us," he explained. "They're mainly planning on serving Grok and Tesla workloads... what I think they are unlikely to do is what we're doing [as] an energy and infrastructure player."

While the space data center industry remains largely theoretical, dependent on unproven technology and massive capital investment, Starcloud's funding success demonstrates investor confidence in orbital computing's long-term potential. The company's early hardware deployments provide valuable real-world data as the industry awaits the launch cost reductions that could make space-based data centers economically viable.

⚡ Trends for the Future

AI chip startup Rebellions raises $400 million at $2.3B valuation in pre-IPO round

South Korean AI chip startup Rebellions has secured an additional $400 million in funding just months after its successful Series C round in November. The pre-IPO funding round was led by Mirae Asset Financial Group and the Korea National Growth Fund, bringing the company's valuation to approximately $2.34 billion.

Founded in 2020, Rebellions operates as a fabless semiconductor company, designing AI chips specifically for inference computing while outsourcing fabrication. Their chips enable AI models to respond to user queries, a capability that has become increasingly critical as large language models mature and see widespread commercial deployment.

The company has experienced remarkable fundraising momentum, raising $650 million in just the past six months. After closing a $124 million Series B in 2024 and a $250 million Series C in November, Rebellions' total funding now reaches $850 million.

Alongside the funding announcement, Rebellions unveiled two new AI infrastructure platforms: RebelRack and RebelPOD. RebelPOD serves as a production-ready inference compute unit, while RebelRack integrates multiple racks into scalable clusters designed for large-scale AI deployment.

The startup is aggressively expanding globally, establishing entities in the United States, Japan, Saudi Arabia, and Taiwan. Chief Business Officer Marshall Choy, who leads the expansion efforts, indicated the company plans to target cloud providers, government agencies, telecom operators, and neoclouds in the U.S. market.

"AI is now measured by its ability to operate in the real world at scale, under power constraints, and with clear economic return," said CEO Sunghyun Park. "That shifts the center of gravity toward inference infrastructure and software that makes that infrastructure usable."

Rebellions represents part of a new generation of chip startups challenging Nvidia's market dominance. As competition intensifies, major tech companies including AWS, Meta, and Google are also developing their own chip solutions, creating a more diverse semiconductor landscape.