Architecture before accumulation
Start with workloads, constraints and ownership. Decide which components belong in the system and which complexity it can do without.
Connected devices, cloud platforms, AI and data systems rarely work in isolation. We design their boundaries, build the parts and make them work together.
Connect equipment to the systems people use. Device integration, telemetry ingestion, fleet applications and role-based access.
Design the infrastructure behind the application. Cloud platforms, compute, managed databases, storage and the services that keep them operating.
Bring models into working systems. AI integration, inference optimisation and GPU engineering, alongside ongoing research into language-model training.
Make data usable across the business. Ingestion, processing pipelines, data platforms and analytics that connect operational information to decisions.
A telemetry platform needs more than device connectivity. An AI application needs more than a model. A cloud platform needs more than infrastructure. We work across those layers, with the application, its operators and the business requirements in view.
Start with workloads, constraints and ownership. Decide which components belong in the system and which complexity it can do without.
Treat APIs, identity, data contracts and failure handling as engineering work. Define what happens at each boundary, including when a dependency is unavailable.
Plan deployment, observability, recovery and access alongside application behaviour. Make the system understandable to the people who will run it.
Cloud infrastructure and developer tooling. Each product has its own users, development path and purpose.
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