Three years ago, we started hearing the same question from aerospace engineers, cloud architects, and satellite operators: “We’re planning something in orbit-where’s the software to help us figure this out?”

The answers weren’t great. Thermal analysis meant cobbling together academic MATLAB scripts. Latency modeling required building custom simulators from scratch. Conjunction screening meant parsing archaic data formats and hoping your propagator was accurate enough. Everyone was reinventing the same wheels.

Meanwhile, the space industry was accelerating. Launch costs dropped below $2,000/kg. Starlink proved you could operate thousands of satellites as a coordinated system. And serious people started talking about putting data centers in orbit-not as science fiction, but as engineering projects with timelines and budgets.

We kept waiting for someone to build the software layer. Nobody did.

So we’re building it ourselves.

The gap we’re filling

If you want to evaluate whether a software workload makes sense to run in orbit, you’re facing a research project. You need to model thermal behavior in vacuum (counterintuitive if you’re used to terrestrial cooling). You need to simulate latency through a constellation (ground stations, ISL hops, processing delays). You need to estimate power budgets across eclipse cycles. And you need to do all of this before you can even have an informed conversation about cost.

Each of these problems has been solved-in isolation, by different teams, with different tools. There’s no integrated environment where you can input workload characteristics and get back a feasibility assessment.

That’s what we’re building with the Orbital Compute Suite.

On the space intelligence side, the problem is different but equally fragmented. Operators need to track their assets and avoid collisions. Analysts need to understand what’s happening in increasingly crowded orbital regimes. Developers building space-aware applications need reliable data APIs. The existing solutions are either government-operated (with access restrictions) or narrowly focused on specific use cases.

That’s what we’re building with the Orbital Intelligence Platform.

Our approach

We’re not trying to replace flight dynamics software or mission planning systems. Those tools exist and they’re good at what they do. We’re building the layer above-the software that helps you answer strategic questions before you need detailed mission design.

Should we consider orbital compute for this AI training workload? What orbits make sense given our latency requirements? How does the collision risk picture look for this orbital regime over the next decade? These are the questions we’re focused on.

We’re also building for developers first. Every capability we ship has an API. If you’re integrating orbital awareness into your application, you shouldn’t need a PhD in astrodynamics. You should be able to call an endpoint and get back useful data.

What’s next

We’re launching the Orbital Compute Suite and Orbital Intelligence Platform in Q1 2026. We’ve been running early access with a handful of teams-satellite operators, cloud infrastructure companies, and aerospace startups-and the feedback has shaped what we’re building.

If you’re working on something that touches orbital computing or space domain awareness, we’d like to hear from you. We’re still in the phase where every conversation teaches us something.

The space industry is entering a new chapter. We think software infrastructure will determine who can move quickly and who gets stuck reinventing wheels. We’re building the tools we wish existed.

Want early access? Request a demo or contact us.