Architecture review
An independent read on a system you are about to build, have just inherited, or suspect is about to become expensive. You get findings and trade-offs, not a sales pitch.
What we do
Engineering across four disciplines
We build the whole path: the app in someone's hand, the platform behind it, the devices feeding it, and the models that make it smarter. Below is what that looks like in practice.
Mobile
Apps that feel native, because they are
We have been shipping cross-platform mobile from a shared C# codebase since the Xamarin days, and that work now lives in .NET MAUI. The principle has not changed: share the logic, never fake the interface. An app should feel like it belongs on the platform it is running on.
Where a product genuinely needs platform-specific depth, we write native. Most of the time the honest answer is a shared core with native edges, and knowing where that line falls is most of the job.
- .NET MAUI cross-platform apps for iOS and Android
- Fully native development where the platform demands it
- Offline-first data and conflict-aware sync
- Push notifications, background processing and deep linking
- Bluetooth LE, NFC, mapping and geolocation
- Native binding libraries for rugged Zebra and Honeywell devices
- App Store and Play Store submission, signing and release pipelines
We have carried fourteen production apps from Xamarin to .NET MAUI, so migrations are familiar ground, not a first attempt. See the work
Web
Platforms built to be integrated against
Most web work is not a website. It is a system with users, data, permissions and half a dozen things that need to talk to it. We build on ASP.NET Core and Blazor, with modern TypeScript front-ends where a richer client makes sense.
Performance and accessibility are not a polish phase. They are constraints we design against from the start, and measure (this site included).
- ASP.NET Core and Blazor web applications
- Modern TypeScript front-ends and progressive web apps
- REST and GraphQL APIs designed for real consumers
- Content management and e-commerce integration
- Identity, authentication and role-based access with Entra ID
- Accessibility to WCAG 2.2 AA and Core Web Vitals budgets
Internet of Things
Devices are easy. Fleets are the hard part.
Getting one sensor to report a reading takes an afternoon. Getting ten thousand of them to stay online, stay secure, and stay updatable for five years is a different discipline, and it is the one that decides whether an IoT project succeeds.
We build device-to-cloud systems on Azure IoT Hub, with the provisioning, monitoring and update paths designed in from the beginning rather than retrofitted after the first field failure.
- Device-to-cloud telemetry with Azure IoT Hub and Event Hubs
- Device provisioning, identity and certificate lifecycle
- Edge processing and offline-tolerant buffering
- Over-the-air updates and remote diagnostics
- Bluetooth LE, NFC and industrial protocol integration
- Telemetry pipelines, time-series storage and operational dashboards
- Precision agriculture: soil, moisture and water-quality monitoring
- Hydroponics and controlled-environment monitoring and control
Artificial Intelligence
AI where it earns its cost, not everywhere
The useful question is rarely "can we add AI to this?" It is "which specific task here is slow, expensive or judgement-heavy enough to be worth a model?" We are happy to tell you when the answer is none. That conversation costs you less than the alternative.
Where it does fit, we build it properly: retrieval grounded in your own data, evaluation so you know whether it is actually working, and a cost model so the bill does not surprise you in month three.
- LLMs through Azure OpenAI and Microsoft Copilot integration
- Retrieval-augmented generation over your business data
- Azure AI Search, vector indexing and embedding pipelines
- Document intelligence, extraction and classification
- Agents and tool-calling through MCP (Model Context Protocol) and Copilot Skills
- Computer vision: pose and body-language modelling for threat detection
- Evaluation harnesses, guardrails and human-in-the-loop review
- Token and cost modelling before you commit
Consulting & training
Sometimes you need judgement, not hands
Not every engagement is a build. A decade of architecture and Agile delivery (and a resident Microsoft MVP) means we are often more useful reviewing a design, unblocking a team, or teaching your developers the stack we work in every day.
Technology selection
Framework, platform and vendor decisions argued against your actual constraints (team skills, budget, timeline and what you already run) rather than against fashion.
Agile & Scrum coaching
Practical delivery process for teams that want to ship more predictably. On-site coaching, plus formal training through our partner network.
Developer mentoring
Pairing, code review and engineering-practice work that raises the floor of an existing team. The goal is that you need us less over time, not more.
AI adoption & enablement
Helping a team use AI well, not just enthusiastically: where tools like GitHub Copilot and Claude genuinely speed up real work, where they do not, and the code review and testing discipline that keeps AI-assisted output held to the same standard as everything else. Increasingly that includes wiring up MCP servers and Skills so an agent can actually act on your systems, not just talk about them.
Cloud & Azure guidance
Migration paths, landing zones and cost control. Which workloads belong in the cloud, which do not, and what the bill will realistically look like.
Engineering practices
CI/CD, automated testing, observability and release process: the infrastructure that decides whether a team can move quickly without breaking things.
.NET, MAUI & Blazor training
Hands-on courses and workshops in modern .NET, C#, .NET MAUI and Blazor, taught by people who ship production systems in them, not just slides about them. Tailored to your team's level and your own codebase.
Architectural guidance & training
Beyond a one-off review: ongoing architectural mentorship and training that leaves your team able to make sound structural decisions themselves: patterns, trade-offs and the reasoning behind them.
Not sure which of these you need?
That is a normal place to start. Tell us the problem and we will tell you what we think it actually is.