Satlyt announced an $8 million seed funding round on October 13, 2026 to deploy artificial intelligence and edge computing software directly onto orbiting satellites, aiming to address downlink bottlenecks and the computational constraints of spacecraft.
The round was led by Houston-based venture capital firm Non Sibi Ventures, with participation from TLcom Capital, Antler, Slauson & Co., Launch Africa Ventures, and Enza Capital. Founded by former Google Cloud and SpaceX product manager Rama Afullo, Satlyt maintains dual headquarters in Sunnyvale, California, and Nairobi, Kenya. Rather than building spacecraft, the company operates a hardware-agnostic software framework that converts disparate orbital computing hardware into coordinated, virtual space data centers and executes AI workloads across third-party satellites.
Satlyt’s technology and flight demonstrations
Satlyt’s software runtime performs machine learning inference at the orbital edge, processing imagery, telemetry and system logs locally to reduce the volume of data sent to ground stations. In an earlier flight validation, the company ran Google DeepMind’s Gemma open-weights AI model aboard a Momentus Vigoride orbital service vehicle and reported compressing onboard software error logs by more than 60% prior to terrestrial transmission.
The company’s most recent software deployment launched on a SpaceX Falcon 9 rideshare mission carrying the TakeMe2Space MOI-1A orbital computing satellite. That flight is operating alongside prototype payloads testing space-based hardware for Google’s Project Suncatcher orbital data center.
Commercial customers and planned demonstrations
The current orbital mission carries a mix of commercial and civil workloads, including research software funded through a NASA Glenn Small Business Technology Transfer (STTR) project to test space cloud computing protocols, edge-vision tracking software for orbital surveillance firm Stellerian, and application hosting for TakeMe2Space. Over the coming year, Satlyt plans to demonstrate distributed computing tasks synchronized across multiple satellites and is targeting integration aboard 20% of active orbital spacecraft by 2030.
