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HK satellite maker Uspace shifts to AI at new Shenzhen tech center

Uspace Technology Group will open an AI application technology center in Shenzhen as it shifts its satellite business focus.

The company, previously known as Hong Kong Aerospace Technology Group, moved its headquarters from Hong Kong to Guangzhou earlier this year.

A unit, Gang Hang Ke, will lead the setup of the new center, which will work on intelligent decision-making and AI-driven processing for satellite remote sensing data.

Uspace developed and launched 12 satellites in 2021 under its Golden Bauhinia Constellation project and plans to produce and launch the remaining satellites in the network before 2026.

🔗 Source: South China Morning Post

🧠 Food for thought

Implications, context, and why it matters.

Golden Bauhinia’s operational scale and funding remain unclear despite 2026 expansion claims

  • Uspace says it has launched 12 satellites for Golden Bauhinia. The firm planned 100+ before 2026, yet as HKATG it had only 10 launched by August 2023 and booked zero remote sensing revenue in 2022 1.
  • Valued at about $320 million, the company offers no secured financing in 1 or a detailed launch schedule for 88+ more craft before 2026.
  • HKATG’s satellite factory opened in 2023 to target 200+ units a year. That adds capacity, though 1 gives no funding or customer contracts for Golden Bauhinia.

China’s AI buildout opens doors for geospatial data providers

  • China’s National Supercomputing Center in Jinan has about 2,000 petaFLOPS (PFLOPS) of AI compute and plans to register 128 large models, which could support satellite data processing 2.
  • Cloud providers or Machine Learning Operations (MLOps) platforms can pursue Shenzhen agencies on AI remote sensing to win contracts as the city rolls out smart city projects that need real-time geospatial analysis.
  • Geospatial analytics firms can bridge operators like Uspace with uses in urban planning, infrastructure monitoring, or environmental assessment across the Greater Bay Area’s 11 city clusters 1.

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