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Satlyt
Sunnyvale and Nairobi company that builds software so AI models can run on other companies' satellites, including onboard decisions that shrink what has to be sent to the ground.
Spacecraft operators who want a model running on the satellite they already fly, so less raw data has to come down on the downlink.
Buyers who need a multi-satellite compute cloud this year, or anyone looking for an orbital data center Satlyt itself will launch.
Verdict
Satlyt, with offices in Sunnyvale and Nairobi, builds software that runs AI models on other companies' satellites. Co-founder Rama Afullo, who previously worked in Google's cloud business and briefly at SpaceX Starlink, left to build that layer after both companies passed on the idea internally. Operators use it to make decisions on the spacecraft and to shrink what gets sent to the ground. On a Momentus spacecraft, Google DeepMind's Gemma model cut a transmission about onboard software errors by more than 60 percent. That saving is the point for operators who pay for downlink.
On October 1, 2026, TechCrunch reported an $8 million seed round led by Houston-based Non Sibi Ventures. Satlyt has flown the software on two demonstration missions. A further flight, on a SpaceX rocket alongside Google's Project Suncatcher prototype, puts the software on a spacecraft from TakeMe2Space. TechCrunch describes three customers on that mission: NASA, which is paying to test protocols for cloud computing in space; Stellerian, which wants to test image-processing workloads; and TakeMe2Space itself. The next project is a shared computing system across two different satellites, which the company expects to attempt next year. Satlyt is not building its own spacecraft (TechCrunch).
Score Breakdown
How Satlyt scores in the categories that matter to its buyers.
Pricing
Satlyt's offer is software on satellites other companies fly. TechCrunch reported an $8 million seed round (TechCrunch).
The Field at a Glance
Where Satlyt ranks among Edge & on-device AI vendors we reviewed, by Overall Score and relative typical engagement cost.
Satlyt scores 6.5 in this peer set, just above Mythic (6.4) and below Axelera AI (7.5) and SiMa.ai (7.7). Relative cost sits with a specialized onboard software deployment, under a chip-platform engagement.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Run a model on a satellite already in the design | Strong | The Momentus flight ran Gemma onboard. |
| Shrink downlink of error and sensor data | Strong | The Gemma run cut one error transmission by more than 60 percent. |
| Host another company's workload in orbit | Mixed | The TakeMe2Space flight is the current test of that. |
| A cloud spanning two satellites | Weak | That demonstration is planned for next year. |
| Buying a spacecraft from Satlyt | Weak | The company does not build the satellite. |
Who it’s for
Good fit
- Satellite operators who lose money sending raw data to the ground
- Spacecraft builders who want a software layer on a processor they already fly
- Teams testing onboard image processing or anomaly handling
Poor fit
- Buyers who need orbital capacity they can schedule this quarter across many satellites
- Companies that want Satlyt to launch the hardware
- Ground software teams with no path onto a spacecraft
Review Excerpts
Below are excerpts from public reviews and coverage. Paid reviews and pay-for-play sites such as Clutch were excluded.
“Satlyt runs on a satellite someone else already flies. On the Momentus flight, Gemma cut an error transmission by more than 60 percent, so less of that report had to be sent to the ground.”
“The way to think about it is that we turn your satellite into a revenue-generating managed service.”
“Satlyt has two demonstration flights behind it, and the cloud that spans two satellites is still planned for next year. I cannot put a workload on that shared cloud this quarter.”
Methodology
This page is an independent evaluation of Satlyt for buyers comparing options in edge & on-device ai. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Satlyt did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.
- Buyer outcomes (for edge & on-device ai)
- Software that runs models onboard
- Path to a shared orbital cloud
- Flights already completed
- What a buyer can purchase now
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.
Scope
Satlyt is graded here as edge & on-device ai. Criteria scores can move as more review volume and product checks are added.