AI/ML & Data
Quantising vision models for sub-5 W edge inference
How much accuracy a detection model actually loses on the way from a workstation GPU to an embedded accelerator, measured across four quantisation strategies and three target boards.
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Research & Whitepapers
We publish what we learn. Benchmarks, methods and failure modes from live programmes — written for engineers, not for procurement.
Published Work
Notes from the bench
Each paper comes out of work we actually shipped. Where a result is inconvenient for us, it is in there too — a benchmark that only reports wins is marketing.
IoT & Embedded
Secure boot and rollback protection on cost-constrained MCUs
A reference chain of trust for parts without a dedicated secure element, covering key storage, signature verification timing and the failure modes an attacker actually reaches for.
GIS & Spatial
Change detection over cloud-heavy regions using SAR and optical fusion
A processing approach for monsoon-affected geographies where optical archives are unusable for months at a time, with accuracy measured against ground survey.
Cyber & Forensics
Threat modelling for connected industrial hardware
A practical method for teams shipping devices into OT environments: what to model, what to skip, and how to keep the model alive after the architecture freezes.
Simulation
Calibrating digital twins against sparse field telemetry
Keeping a plant or network twin honest when sensors are few, noisy and occasionally offline — with calibration error measured against held-out field data.
Hardware
EMI-aware layout for mixed-signal sensor front-ends
Grounding, return paths and stack-up choices that decide whether a board passes pre-compliance the first time, with measured before-and-after scans.
Papers are shared on request so we can answer questions alongside them. Tell us which one you need and what you are building.
Bring us the problem behind the paper.
If one of these touches what you are building, the fastest next step is a conversation with the engineer who wrote it.