MRO intelligence, edge avionics, and UAV autonomy — civil-first
Aerospace AI operates under the most demanding software assurance standards in any industry. We help MRO operators, avionics suppliers, and UAV makers deploy AI that is architecturally compatible with DO-178C, DO-254, and ARP4754A — from MRO copilots over technical manuals to automated NDT visual inspection and edge inference in avionics. Our focus is civil aviation and UAV; military programmes are out of scope.
We design aerospace AI with the assurance pathway in mind from day one — separating AI-assisted (information only) from AI-commanded (safety-critical) functions, choosing architectures that admit verification under DO-178C, and building the data infrastructure that feeds retraining without compromising model traceability. Capability-only engagement: we bring transferable primitives from industrial edge AI and apply domain expertise; we do not claim existing aerospace operator contracts.
Where we engineer — from perception to mission, on the aircraft and on the ground. Certification-aware throughout (see the note above).
Vision-based localisation and obstacle awareness where GNSS is denied or unreliable.
Fusing camera, LiDAR, IMU and radar; perception on-board within power and thermal budgets.
Vision-language models on the aircraft for scene understanding, behind a deterministic safety boundary.
Route, task and contingency planning with human-on-the-loop oversight.
Automated defect detection for assets, and maintenance models for the fleet itself.
Fleet coordination, ground-control integration and telemetry pipelines.
Sim-first validation, digital twins, and AI for NDT and assembly quality.
Hyperion provides architecture, engineering and production-readiness support. Formal aviation certification activities require appropriately qualified specialists and approved processes.
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.