Side-by-side comparison of AI visibility scores, market position, and capabilities
Space startup deploying orbital mirrors to extend solar farm output after sunset. $20M Series A; seeking FCC approval for Earendil-1 test satellite in 2026.
Reflect Orbital is a space energy startup with an audacious mission: deploy networks of orbital mirrors to reflect sunlight onto solar farms after sunset, effectively extending renewable energy generation hours without battery storage. Founded to solve the intermittency problem plaguing solar power, the company is developing small satellite constellations that track ground-based solar installations and redirect sunlight as the Earth rotates away from the sun.\n\nThe company's flagship program, the Earendil-1 test satellite, is awaiting FCC approval for a planned 2026 demonstration mission. If approved, Earendil-1 will validate the core optical redirection and satellite-to-ground alignment technology at scale. The platform targets utility-scale solar operators and grid operators looking to reduce curtailment and storage costs through a space-based complement to ground infrastructure.\n\nReflect Orbital raised a $20M Series A to fund its satellite development and regulatory strategy. The FCC approval process for Earendil-1 represents the company's critical near-term milestone; a successful 2026 demo would de-risk the technology and position Reflect Orbital as a pioneering player in the emerging orbital energy infrastructure market, which sits at the intersection of NewSpace economics and the global clean energy transition.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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