By Avi Shabtai, CEO of Ramon.Space 

For many years, scaling compute followed a clear path: build larger facilities, pack in more hardware, add more power and cooling. That approach worked when workloads were relatively stable and growth was gradual. Today, it is no longer sufficient.

AI, space-based systems, and real-time global services are driving compute requirements that exceed what Earth-based infrastructure was designed to support. This is not because innovation has slowed, but because the underlying physical and architectural assumptions of modern data centers are being stretched beyond their limits.

This is not only a software issue. It is a matter of physics and system design.

Earth is becoming the limiting factor

Data centers today are increasingly constrained by their physical environment. Securing large amounts of continuous power is becoming more difficult as grids face congestion, energy prices fluctuate, and sustainability requirements increase. What was once taken for granted - reliable power at scale - is now a critical challenge.

Cooling is another major constraint. As compute density increases, heat removal becomes one of the most complex and expensive aspects of operating a data center. Higher ambient temperatures, water limitations, and more frequent extreme weather events are making thermal management a primary design consideration rather than an afterthought. On Earth, a significant portion of effort and cost is spent managing heat rather than advancing capability.

There are also practical constraints around location and deployment. Suitable sites are limited, permitting timelines are long, and facilities are increasingly exposed to natural disasters. Expanding terrestrial compute has become slower, more expensive, and less resilient.

These challenges are structural, not temporary.

AI is highlighting architectural gaps

AI is accelerating demand for compute, but the issue goes beyond energy consumption or scale.

AI systems generate large volumes of data and increasingly depend on inputs from distributed sources, including satellites and edge platforms. Much of this data is time-sensitive and inefficient to move back and forth for centralized processing.

Traditional data centers were designed for predictable workloads and constant human oversight. They were not built to support autonomous systems operating across space and Earth as a single environment. As AI systems evolve, the limitation becomes one of architecture rather than algorithms.

Supporting these systems requires compute that operates closer to where data is generated and can function reliably without continuous interaction with the ground.

Space offers a different operating environment

Space fundamentally changes the operating conditions for compute.

In orbit, energy is continuously available. Solar power is abundant and not subject to grid congestion, peak pricing, or land-use constraints. For energy-intensive workloads, this removes a major limitation.

Thermal management is also more straightforward. Space provides a stable environment for heat rejection through radiation, rather than relying on air or water. Instead of compensating for environmental variability, systems can be designed around predictable physical conditions.

Space-based infrastructure is also less exposed to many of the risks faced on Earth. It is not affected by hurricanes, floods, heat waves, or earthquakes, and it avoids many geographic and regulatory constraints that slow terrestrial deployments.

This is not a future concept. It is a different, well-understood operating environment.

A new era of compute

This is not about extending terrestrial architecture. It is about entering a new era of computing.

A meaningful and growing share of global compute will occur in space.

Certain workloads already make sense in orbit: latency-tolerant AI training, Earth-observation data processing at the point of collection, large-scale simulation, batch analytics, and sovereign workloads constrained by energy or cooling on Earth.

Beyond that, some services are inherently space-native. Autonomous satellite operations, real-time Earth analytics, in-orbit coordination, responsive space infrastructure, and space-domain awareness depend on compute that runs continuously and close to the source. These systems are not simply improved by space-based processing - they require it to scale.

As space systems grow more autonomous and interconnected, compute in orbit will shift from an efficiency advantage to a core requirement.

Data centers in space will be distributed 

Space-based compute will not take the form of a single, centralized facility. It will be built as a distributed network of modular, autonomous data centers designed to scale incrementally and operate reliably over long missions.

Processing data in orbit changes how systems operate. Instead of transmitting large volumes of raw data to Earth, information can be processed, filtered, and acted on where it is generated. This reduces latency, lowers downlink requirements, and improves overall efficiency.

To support evolving services, this infrastructure must be managed through software. Compute resources need to be allocated, updated, and reused over time so systems can adapt without requiring new hardware launches. Hardware provides capability, but software enables flexibility.

Enabling data centers in space

This is the focus of Ramon.Space.

Ramon.Space enables data centers in space by providing software-defined in-orbit computing infrastructure that supports long-duration, space-based services and applications. Today, we work with customers deploying advanced space systems that require onboard processing, autonomy, and flexible compute architectures.

The emphasis is not on hardware alone. It is on building a compute platform that allows orbit to function as a programmable, scalable environment.

By managing processing, storage, and connectivity directly in orbit, we enable customers to run multiple services, adapt to changing mission requirements, and evolve their systems over time. Onboard data processing increases autonomy, reduces dependence on downlink capacity, and unlocks new operational models.

Compute is no longer confined to a single domain.

We are entering a phase where a massive portion of computing - particularly for AI-driven, space-connected, and autonomous systems - will take place beyond Earth.

Terrestrial data centers will remain critical. But they will no longer be the exclusive center of gravity for compute.

The systems being built today - in AI, autonomy, and space infrastructure - are already pointing in this direction.

Data centers were never meant to stay on Earth.

About the Author

Avi Shabtai | CEO of Ramon.Space 

Avi Shabtai is the CEO of Ramon.Space, a global leader in space computing infrastructure. He brings extensive experience in business and technology leadership, with a focus on the space sector, and a career spanning both startups and publicly traded companies across data centers, networking, semiconductors, and wireless communications. Avi has a strong track record in deep technology innovation, having led multiple global technology companies throughout his career. 

Prior to joining Ramon.Space, he served as CEO of MultiPhy Inc., a company specializing in high-speed integrated circuits for the data center market. He previously held executive roles including VP and GM at Alvarion Technologies (ALVRQ), VP of R&D at Tiaris, and Director of Engineering at Metalink (MTLK). He holds both an MSc and a BSc in Electrical Engineering from the Technion – Israel Institute of Technology and is an SMP graduate of the Technion Institute of Management.