The technology we build on,
and why we chose it.
Twenty-one technologies across five layers of the stack — backend, frontend, data, cloud and BI — all run in production by the same senior team for 9+ years. Chosen because they hold up as a product grows, not because they were trending.
What a wrong stack
costs you later.
Technology choices are cheap to make and expensive to unmake. These are the four we get called in to unpick most often — and what the rest of this page is written to avoid.
A stack picked around who was free
The technology gets chosen to fit whoever the vendor had on the bench that month — not to fit what your product actually has to do.
One specialist who holds all the knowledge
A single contractor knows the framework and nobody else can maintain it. When they move on, your product becomes a risk rather than an asset.
Licences and lock-in nobody priced in
A platform that was cheap to start on and expensive to leave, with your data sitting in a format only that vendor can read.
A rebuild eighteen months in
The stack that got the MVP out of the door can't take the data volume, the traffic or a second team — so the whole thing gets written again.
The right stack is the one
you can still run in 2030.
We are not loyal to any of these technologies. Each one earned its place by doing a specific job well in production, and the recommendation you get is the one that fits your product, your data and the team who will live with it after we hand over.
Mainstream technology, chosen on purpose.
Nothing here is exotic. Every layer is built on technology with a large community, a long support horizon and a deep talent pool — so your product is never dependent on a niche tool, or on us specifically, to keep running.
Fit before fashion
A reporting product, a trade-data platform and a marketing site want genuinely different trade-offs. We pick per project and write down why, so the reasoning outlives the decision.
One team across every layer
The same senior engineers work from the database to the interface. You are not waiting on a specialist to become available before the next piece can start.
Boring where it counts
Mainstream, well-documented, widely-hired-for technology. If we stopped working together tomorrow, your team could pick this up — that is the test every choice has to pass.
AI-accelerated, senior-led
AI tooling compresses the mechanical part of a build. The judgement about what should be built, and on what, still comes from people who have shipped it before.
Five layers,
one senior team.
Backend
The services, APIs and pipelines behind the interface. Python does the data and AI work; .NET and Node.js pick up the jobs where the ecosystem — or the team already running it — makes them the sensible choice.
Explore backendFrontend
The part people actually use. React is our default for interactive, data-heavy products, with Next.js, Tailwind and Angular where the product needs to rank, stay visually consistent, or run for a decade.
Explore frontendDatabase
Where the data lives and how quickly you can ask it a question. Relational, document, lakehouse and columnar are genuinely different tools — we match them to the shape of your data rather than to habit.
Explore databaseCloud & DevOps
Hosting, environments and the deployment story. Azure, AWS or GCP depending on where your business already sits and what it already pays for, with GitHub Actions automating the pipeline on all three.
Explore cloud & devopsBI & Analytics
The layer decisions get made on. Power BI for governed enterprise reporting, Highcharts when the visualisation has to live inside your own product, Databricks AI/BI for asking a lakehouse questions in plain English.
Explore bi & analyticsNot sure which stack fits? Ask the engineer who'd build it.
Book a 30-minute working session with a senior engineer — a real conversation about your product and the trade-offs, not a sales call.
Built with clients
who measure outcomes.
“The best stack is the one your team can still run in three years without us. We pick mainstream technology and write it so someone else could pick it up — because eventually someone else will.”
I like High Digital because they do what we need effectively and within our budget.Read more client stories
More on how we build.

Agentic AI vs RPA vs Workflow Automation: Which Does Your Process Need?
Week 3 of the High Digital Workflow Automation Series. Workflow automation, RPA and AI agents solve different problems. Here’s how to tell which one a process needs, and why the best answer is often all three.
Read more
High Digital Earns OpenAI ChatGPT & Codex Solutions Practitioner Recognition
High Digital has earned both ChatGPT Solutions Practitioner and Codex Solutions Practitioner recognition from the OpenAI Partner Network.
Read more
Zapier vs Make vs n8n vs Power Automate: What Workflow Automation Really Costs in 2026
Week 2 of the High Digital Workflow Automation Series. Each platform bills on a different unit, so headline prices mislead. We run one real workflow through all four to show what you’d actually pay.
Read moreQuestions, answered straight.
Have an outcome in mind?
We'll help you
ship it.
- You're building a data product and need a team that can deliver.
- You want to get AI-ready — pragmatically, not theoretically.
- Your reporting is a mess and you need a real platform underneath it.








