Embedded problems are rarely algorithmic. They are usually the accumulated cost of decisions made early, under schedule pressure, by people who have since left. By the time we are called, the symptom is a board that works on the bench and fails in the field, or a codebase nobody is willing to change.
What the work is
Board bring-up and hardware validation
First power-on through to a booting, instrumented system. Finding out whether a fault is silicon, layout, supply or software, which is where most schedule slips actually happen.
Driver and kernel-side development
Device drivers, kernel modules and the userspace interfaces around them. Including the awkward cases: unusual buses, vendor silicon with thin documentation, and hardware that does not behave as its datasheet claims.
Streaming and communications stacks
Video, sensor and telemetry paths where throughput, latency and jitter all matter at once, and where a working prototype does not imply a working product.
Long-lifecycle maintenance
Security patching, toolchain migration and component end-of-life response on products already in service. Unglamorous, and the reason a fifteen-year product remains sellable.
Recovery work
Firmware nobody currently understands, with no original author and no documentation. We read it, document it, and make it safe to change.
Where an engagement usually starts
Most engagements start with a fixed-price assessment: we take the hardware and the code, establish what actually works, and produce a written account of the state of the system with the risks ranked by cost. That is useful whether or not you then hand us the work.
What we do not do
We are not an app or web development team, and we do not take on pure cloud backend work. If the problem does not need somebody who understands what the hardware is doing, we are the wrong firm.
Related practices
Problems here usually touch these too
02
Photonics & Industrial Vision
Optics, illumination and imaging chains, from sensor selection through to a working inspection result.
03
Industrial AI & Edge Computing
Inference where the data is, sized for real hardware and real power budgets rather than a benchmark.
04
Embedded Linux & Edge Platforms
BSPs, Yocto builds, RTOS decisions and the platform work everything above it depends on.
Bring us the challenge
The one that has been handed back, sits between two suppliers, or nobody can say is possible yet. A short call costs you nothing and you will speak to one of our consultants.
Engineer to engineer. No handoffs.