Service

Application Modernization

We modernise legacy applications incrementally: assessment, strangler-fig migration, dependency and platform upgrades, test coverage, and a path back to safe, frequent releases.

Core stack
Java · Spring Boot · Kotlin · Node.js · PostgreSQL

Legacy is not an insult — it is a system that made money

The problem is rarely age. It is that the cost of changing the system has grown until every release needs a committee. Modernisation is about lowering that cost, in increments, while the business keeps running.

The sequence we normally follow

  1. Assess. Runtime versions, dependency risk, test coverage, deployment path, hot spots by change frequency, and tribal knowledge concentration.
  2. Stabilise. Reproducible builds, a characterisation test suite around critical paths, deployment automation.
  3. Extract. Peel off bounded slices behind a facade, one at a time, each one releasable and reversible.
  4. Retire. Delete the old path only after the new one has carried real traffic.

What we refuse to do

Start a two-year rewrite with no intermediate value. The single most common cause of a failed modernisation programme is a plan whose first delivery is at the end.

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.

fintech2025
  • Java
  • Spring Boot
  • Kotlin

01European payment service provider (sample scenario)

Payment Platform Modernization

A ten-year-old payment monolith moved from quarterly release windows to weekly deployments, without a rewrite and without a settlement incident.

  • Release cadence moved from quarterly windows to weekly deployments
  • Reconciliation lag reduced from overnight to near real time
  • Java
  • Spring Boot
  • Kotlin
  • PostgreSQL
  • Kafka
travel and hospitality2025
  • Kotlin
  • Spring Boot
  • PostgreSQL

02Multi-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

FAQ

Application Modernization — common questions

01Rewrite or refactor?

Refactor by default. Full rewrites are justified when the runtime is unsupported, the domain has fundamentally changed, or the system has no tests and no living knowledge — and even then we migrate in slices behind a facade.

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.