Most EdTechs show testimonials. We show systems.
Every project below is real — built for aerospace, manufacturing, and industry. This is the standard apprentices are trained to.
Projects
Physical AI for Design & Material
Applied R&D with a global Tier-1 automotive manufacturer · 2022–2026
CAD goes in, a graph neural network learns the part’s physics, and the shape itself becomes something an optimiser can search — in minutes.
View caseSatellite Telemetry Anomaly Detection
German Aerospace Center (DLR), Köln · 2021
Catches failure precursors in satellite telemetry — and refuses to trust its own alarm when the evidence is contaminated.
View caseBEWiS — Weightless Neural Networks on GPU
Fraunhofer FKIE, Wachtberg · 2019–2020
Real-time background subtraction that learns what "normal" looks like from the video itself — no training set, no labels.
View casePhysical AI for Process
Applied R&D with a global Tier-1 automotive manufacturer · 2022–2026
You bring the CAD. The geometry is never assumed — the process window is optimised for the part you actually upload.
View caseBlow-Mould Wall Thickness — FEM in Seconds
Applied R&D with a global Tier-1 automotive manufacturer · 2022–2026
A neural network reproduces a 45-minute finite-element wall-thickness simulation in seconds — and the comparison shows where it still disagrees.
View caseOptimisation
Lab teaching track · used across the design, material and process work
Every project on this page ends in the same question: of all the settings you could choose, which one do you actually run? This is how that gets answered.
View caseLand Decision Engine
Independent build · 2025–2026
Turns "should I hold, build on, or sell this plot — and when?" into a scored, auditable answer.
View caseMarket Research Dashboard
Industry collaboration · 2025–2026
A market analysis platform built to be honest about what it cannot know — and audited until it was.
View case