On-board autonomy, EO edge inference, and constellation operations
Space AI must operate autonomously under the harshest physical constraints in any domain: radiation-altered compute, minutes of latency to ground, and extreme SWaP-C budgets. We help satellite operators, Earth-observation newspace companies, and ground-station teams deploy AI that works on-board and on-ground — from EO image triage at the edge to constellation operations autonomy. Capability-only engagement: we bring transferable edge-AI and autonomy architecture expertise; we do not claim existing space-operator contracts.
We design space AI architectures for the constraints that matter: on-board inference on radiation-tolerant or radiation-aware hardware, EO image triage that maximises downlink value per pass, and ground-station AI that reduces operator load for constellation management. Our edge-AI primitives — proven in terrestrial constrained-hardware deployments — provide the starting point; we adapt for the radiation and SWaP-C envelope.
Based on common industry needs
Four weeks to a strategy document, a business case, an ROI model, and a 12-month execution plan — scoped for industrial operators where OEE, safety-regime timelines, and physical-system procurement cycles are the real constraints, not just board optics
Twelve weeks to a production-grade multi-agent system that serves as the software and control-plane complement to your cyber-physical stack — fleet intelligence, SCADA-adjacent orchestration, or autonomous operations — with the eval harness, the observability stack, and the SRE handoff your team needs to operate it
Twelve weeks to harden an edge or embedded AI pilot stuck before production — on constrained hardware, inside safety envelopes, under latency and reliability requirements the pilot was never designed to meet
Twelve to twenty-four weeks to risk-classify your AI systems, complete the conformity assessment, produce the Annex IV technical documentation, and stand up post-market monitoring — with special depth on Annex III high-risk categories for autonomous, industrial, and robotics deployments
The Full-Stack Physical AI layers most relevant to this sector.
A 30-minute call is enough to diagnose whether your AI initiative is stuck for industry-specific reasons — and what to do about it.