Five service lines — each a complete end-to-end capability, not just a layer of the stack — backed by ten technical domains I keep sharp.
Polished, fast, responsive marketing sites and landing pages. From concept to deployment — design, HTML/CSS/JS, CMS integration, and SEO-ready structure.
Full-stack web platforms with authentication, role-based access, databases, and APIs — built to scale and survive real operational load.
Analytical platforms that turn raw data into decisions — connected to live databases, updated in real time, and designed so non-technical stakeholders can act on them without asking for help.
Cross-platform iOS and Android apps with offline-first capability — ideal for field teams working in low-connectivity environments who need to capture and sync data reliably.
Spatial software for utilities, government, and environmental organisations — from live network maps to satellite-imagery AI pipelines connected to web interfaces operators actually use.
Not sure which service fits your project? Let's talk through it.
Ten domains, one habit of mind: understand the data, then engineer around it.
Not a list of logos — the job each technology does inside a real system.
My go-to for data-heavy web applications — I use Django's ORM, admin interface, and authentication scaffolding to ship enterprise platforms quickly, then extend them with DRF APIs consumed by React frontends or mobile clients.
I build interactive frontends in React for everything from marketing sites to complex admin dashboards — with Next.js for server-side rendering, SEO, and edge-friendly deployments where performance matters.
I use Flutter to ship a single codebase to iOS and Android — useful for field-data collection apps and offline-first tools where a native feel matters and two codebases would slow delivery.
I build data pipelines that extract, clean, and load business data into analytical schemas, then expose them through dashboards with Leaflet, Mapbox, or D3 — so decision-makers see live numbers, not yesterday's spreadsheet.
I use PostGIS to build enterprise spatial databases supporting millions of records — from utility asset registries to parcel-level land records — with sub-second query times on complex geospatial joins.
I use Earth Engine to process decades of satellite imagery at scale — computing NDVI time series, detecting land-use change, and feeding cleaned raster outputs into downstream ML pipelines without managing my own storage cluster.
I train computer-vision models on satellite and drone imagery for land-cover classification, infrastructure detection, and change-detection — deployed behind FastAPI inference endpoints consumed by web dashboards.
I containerise every service and put Nginx in front as a reverse proxy with SSL termination — so a stack developed on a laptop deploys identically on a Contabo or DigitalOcean VPS every time.