Pod Insights Finshots Daily What is the appeal of orbital data centres? About this episode In today’s episode on 8th May 2026, we argue whether putting data centres into space makes sense economically.
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Transcript 0:01 Speaker 00 Hello folks, you're tuned into Finchart's Daily. In today's episode, we argue whether putting data centers into space makes sense economically.
0:12 Speaker 00 But here's a quick side note before we begin. We're hosting a free two-day insurance masterclass that helps you build real financial security by understanding health and life insurance the right way. There are two sessions that we're hosting this Friday and Saturday that is on 8th May and 9th May. And if you'd like to register for free, then you can do so while this is last by going to the link in the description and enrolling for free. Alright, let's get on with today's story. On May 3rd, 2026, Bengaluru-based space tech startup Galaxi launched Mission Drishti. Now, this may sound like just another satellite launch, but the underlying technology is actually quite interesting.
0:50 Speaker 00 Traditionally, satellites have relied on either optical sensors or synthetic aperture radar sensors, that is SAR sensors. Optical sensors work much like a regular camera, capturing visual imagery, while SAR uses radar waves to see through clouds, darkness and poor weather conditions. Both are useful individually, but combining the two creates a much richer picture of Earth. The problem though, is that the data usually comes from different satellites, captured at different times and angles, creating inconsistencies. And that's what Mission Drishti attempts to solve. Instead of merging data later, Galaxi built both sensors into a single satellite so they can observe the same target simultaneously. The real magic, however, happens in the software layer.
1:35 Speaker 00 AI models fuse the data from both sensors into a single unified image with far higher accuracy than conventional approaches. Even after all this, there is still one bottleneck. Most of the heavy computation still happens on Earth, where GPUs process the raw satellite data after it is transmitted back from orbit to terrestrial data centers. But imagine, what if satellites themselves could run data center-grade AI models directly in space? That is exactly what companies are now chasing. And it is where the idea of orbital data centers starts becoming far more than science fiction. Bengaluru-based space startup Pixel announced plans to launch India's first orbital data centre satellite.
2:16 Speaker 00 The satellite, called Pathfinder, is expected to go into orbit as early as next year and will host data centre-grade GPUs directly in space. Its first major workload is expected to involve Sarvam's AI models, which would analyse crops, infrastructure and weather patterns directly in orbit. That last part is what we're going to focus on for now. Because Pathfinder wants to eliminate the entire loop of satellites capturing raw imagery and beaming it back to Earth, where data centres process the information. The idea is to do this processing in orbit itself using AI and transmit only the insights. In theory, that could improve efficiency for applications like defence, weather forecasting, precision agriculture and disaster monitoring.
2:58 Speaker 00 But once you move past the novelty factor, a much larger question emerges. Why would anyone want a data centre floating in space in the first place? Well, the answer begins with three problems the technology industry's slowly running into on Earth. You see, AI infrastructure is becoming extraordinarily resource-intensive. Training and running large AI models now requires vast amount of electricity, cooling infrastructure, land and water. For context, a single hyperscale AI data centre can consume as much as electricity as a small city. And as AI adoption accelerates, governments and companies are beginning to realise that raw computing power itself is becoming a strategic edge. This is where orbital computing starts to sound like an attempt to solve a very real bottleneck. The first advantage is power.
3:43 Speaker 00 Unlike terrestrial solar farms, satellites in orbit can theoretically access near-continuous solar energy without interruptions from weather or night cycles. That means the long-term economics of power-intensive computing potentially attractive, especially if launch costs continue to fall. The second appeal is cooling, because cooling a data centre has become one of the biggest costs in modern computing. AI chips generate enormous amounts of heat and terrestrial data centres spend heavily on cooling systems, often consuming huge quantities of fresh water in the process. Space changes that equation because the vacuum of space can act as a heat sink. However, it is not as straightforward as It sounds, we'll explain why a little later. The third appeal is land. As countries compete to build AI infrastructure,
4:26 Speaker 00 they are also realizing that data centers occupy enormous amounts of physical space and consume substantial electricity and fresh water. And in densely populated countries like India, that raises an important question. Should scarce land and electricity be allocated to server farms that employ relatively few people compared to manufacturing industries or services? So, yes, orbital data centers attempt to sidestep some of those constraints by shifting part of the infrastructure burden into space. However, the moment the concept starts sounding compelling, physics steps back into the conversation. Because putting GPUs in space is far more difficult than putting GPUs on land. To understand why, let's go back to the thermal problem.
5:09 Speaker 00 Modern AI hardware generates intense thermal loads and while the vacuum of space offers theoretical advantages in cooling, heat dissipation in orbit is actually extremely complex. On Earth, server racks can help remove heat through airflow, liquid cooling systems, or water-based heat exchange. In space, there is no atmosphere to transfer heat via convection, so thermal management relies heavily on radiation systems which are slower and technically challenging. Then comes the issue of maintenance. When a terrestrial server fails, technicians replace or repair it relatively quickly. However, in orbit, repairs become vastly more expensive and complicated.
5:51 Speaker 00 Hardware malfunction could potentially render an entire compute node unusable and that creates very different economics compared to traditional cloud infrastructure. Then, there's the radiation problem. On Earth, our atmosphere and magnetic field naturally shield electronics from most cosmic radiation. But in orbit, GPUs are constantly exposed to them. Over time, this radiation can corrupt memory, damage components, and cause bit flips in which tiny changes in data lead to computational errors. However, recent NASA tests on commercial GPUs and TPUs showed that modern AI hardware may survive radiation exposure far better than previously experienced. But that does not eliminate the problem entirely because it is still too early to know
6:35 Speaker 00 how reliable this hardware would remain over long periods in space. Launch costs are another constraint. Even though companies like SpaceX have dramatically reduced the cost of reaching orbit, sending satellites into space remains more expensive than deploying servers on Earth. In fact, the entire economic viability of orbital computing depends on one thing above everything else: launch costs collapsing dramatically over the next decade. Right now, running AI workloads in orbit is staggeringly expensive. To understand just how extreme the economics currently is, running a single 800 equivalent GPU in orbit today is estimated to cost roughly $1.42 per GPU hour, with most of that cost coming from launch.
7:17 Speaker 00 Running that same GPU inside a modern terrestrial data center costs approximately $1 per hour. And if companies manage to survive the enormous upfront launch costs, the operating economics in orbit begins to look surprisingly attractive. Energy generated from uninterrupted solar exposure could potentially become dramatically cheaper over long durations compared to terrestrial electricity markets. At the same time, orbital systems avoid some of the massive freshwater requirements that modern terrestrial data centers struggle with today, which means the future of orbital computing will depend more on whether reusable rockets can make it cheap enough or the economics to finally make sense. And there is a broader concern too. Low Earth orbit is already becoming crowded.
7:59 Speaker 00 Thousands of satellites now operate there and orbital debris is becoming a growing concern. Adding more satellites to an increasingly congested environment introduces long-term operational complexity. This is why we can view orbital computing not as a replacement, at least not yet, for terrestrial cloud infrastructure, but as a specialized extension of it. For workloads tied closely to space-generated data, such as military intelligence, earth observation, or climate monitoring, processing data directly in orbit could make sense. In these cases, speed and resilience matter more than pure cost efficiency. But for mainstream cloud computing, orbital infrastructure still struggles to compete with terrestrial alternatives.
8:40 Speaker 00 Many of the constraints driving this conversation could eventually be solved more economically on Earth itself through better energy systems and more efficient chips. Which means orbital data centers may ultimately occupy a niche. Still, for India, the opportunity is strategically interesting. We already have strengths in space engineering, software talent and a rapidly growing AI ecosystem. If companies like Pixel and Sarvam AI can demonstrate that orbital computing works reliably, India could establish an early position in this emerging infrastructure category. Also, the fact that companies are seriously considering moving computing infrastructure into orbit says something profound about where technology is headed.
9:19 Speaker 00 Our computing demands are becoming so enormous that companies are beginning to look beyond Earth itself for the next frontier of infrastructure. All right, folks, I will see you in the next one.
9:32 Speaker 00 Thank you for listening to today's episode. And if you want to share your feedback or suggestions, do drop us an email to [email protected] . Until next time.
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