Service

Web Application Development

Modern web application development — component architecture, accessibility, performance budgets and interfaces that hold up under production data.

Core stack
TypeScript · React · Astro · Vite · Node.js

The hard part is not the first screen

Demos look great with twelve rows of data. Production has two hundred thousand, inconsistent permissions, half-migrated legacy records and users on a train connection. We build the second kind of interface.

Where we add the most value

  • Data-dense internal tools: operations consoles, admin panels, back offices
  • Customer-facing portals with complex permission models
  • Design system implementation and long-lived component libraries
  • Rescuing frontends that have become too slow or too fragile to change

Standards we hold

Performance budgets agreed up front. Keyboard navigation and screen-reader semantics treated as requirements, not polish. Type safety across the API boundary so refactors are mechanical instead of terrifying.

Case studies

Where this work shows up

Problem, constraint, decision, consequence. No vanity metrics, no logos we are not allowed to name.

All case studies

Sample contentSample engagement. Illustrative scenario used while the site is in build — not a named client project.

travel and hospitality2025
  • Kotlin
  • Spring Boot
  • PostgreSQL

01Multi-property hospitality group (sample scenario)

Enterprise Booking Platform

A booking platform serving multiple properties and channels, rebuilt around a single availability model and a back-office console operators actually wanted to use.

  • Overbooking incidents eliminated in the peak season following launch
  • Channel synchronisation latency reduced from minutes to seconds
  • Kotlin
  • Spring Boot
  • PostgreSQL
  • Redis
  • Kafka
data and analytics2025
  • Java
  • Kafka
  • PostgreSQL

02Analytics provider in the retail sector (sample scenario)

High-Load Data Processing System

A nightly batch pipeline that had outgrown its window, re-architected into an incremental streaming system with correctness checks that alert before customers notice.

  • Processing moved from a single nightly window to continuous incremental updates
  • Single-day reprocessing without re-running the full pipeline
  • Java
  • Kafka
  • PostgreSQL
  • Redis
  • Docker

Start a conversation

Need this kind of work?Start here.

Tell us what you are trying to build, fix or decide. If we are not the right team for it, we will say so and point you somewhere better.

Typical first step: a 30-minute call, then a short written assessment.