Engineering · Hardware
Design the machine, not just the code.
Instruments, embedded systems and the architecture around them. This is the reason our diagnostic systems could be built to a compute budget instead of around whichever accelerator happened to be available that quarter.
Board and electronics design
Schematic capture, layout, signal integrity, power design, design for manufacture. Reviewed for manufacturability before anyone reviews it for elegance.
Embedded firmware
Bare-metal and RTOS firmware, drivers, and on-device signal processing. Update and rollback designed in at the start, not added after the first field failure.
Sensor and instrument integration
Selection, characterisation, calibration, and the data path off the instrument. Characterisation comes first, because a model is only ever as good as what the sensor really produces.
System architecture
Failure behaviour, redundancy, data paths, and the interface between instrument and platform. What happens when a component fails is a design decision, not an incident to be discovered.
Thermal and power
Thermal budgets, power envelopes, and the enclosure constraints that follow. These usually decide the industrial design rather than the other way round.
Compliance engineering
EMC, electrical safety and certification support, scoped to the market the product is going into.
Method
Why a software company does this at all
Treat hardware as procurement and you get a familiar result: a model trained on clean data the shipped instrument never produces, or a pipeline whose timing only closes on hardware nobody wants to buy.
Deciding the sensor, the data path and the compute budget alongside the model avoids both. It is also why our systems can be deployed inside a hospital. A design that assumed unlimited cloud compute cannot be moved into a basement afterwards.