Legacy Modernization
Legacy modernization done in stages, with tests pinning the behaviour that must stay identical and a senior architect signing every step. The method has a headline proof: a 14-year-old Go backend rewritten to Node.js in 6 months by one senior AI-tooled engineer — against typical quotes of around two years — while the system stayed in service.
The free 30-minute session maps your legacy estate — what is fragile, what is fine, what actually blocks the business — and gives an honest modernise-vs-leave-alone read. You keep the map either way.
How legacy actually blocks a business
The system works; changing it is the risk
The old platform runs the business every day — that is exactly why nobody dares touch it. Every postponed change accrues: integrations you cannot do, hires who refuse the stack, features competitors ship. Modernisation is not about the code being old; it is about the change being frozen.
Two people on earth understand it, and one is retiring
Knowledge concentration is the quietest legacy risk. The modernisation that matters here starts with archaeology: documenting behaviour, pinning it with tests, and widening the circle of people who can safely change the system.
The framework is out of support; the auditor noticed
End-of-life runtimes and unpatchable dependencies turn a working system into a compliance finding. Staged modernisation clears the finding without betting the company on a big-bang rewrite.
The last rewrite attempt failed
A parallel green-field build that never caught up with the living system — the classic failure. Our method never runs a parallel product: it modernises the real one, stage by stage, behind stable interfaces, live the whole time.
Serious infrastructure runs for decades. Modernising it is archaeology plus engineering — respect for what works, tests for what must not change.
The method
Behaviour pinned before anything moves
Characterisation tests capture what the system actually does — including the undocumented quirks downstream systems depend on. Identical behaviour becomes provable, not promised.
You get: a test harness that makes every stage verifiable.
Staged replacement behind stable interfaces
Module by module, oldest and riskiest first, each stage shippable and reversible. The business never waits for a big bang, and there is no parallel product to fall behind.
You get: a stage plan with dates, risks and rollback per stage.
AI-accelerated, senior-verified
AI tooling reads and translates legacy code at a pace humans cannot — the 6-months-vs-2-years delta in our anchor case. Every translated module passes senior review and the pinned tests before it ships.
You get: the speed of AI translation with the safety of senior sign-off.
Knowledge out of heads, into artifacts
Architecture documentation, runbooks and decision records accumulate as stages land — the bus-factor fix built into the process.
You get: a system your next hires can safely change.
How it works
Estate assessment
What exists, what is fragile, what blocks the business — read from the code and the people, written up with a modernise-vs-leave-alone verdict per component.
Pin and stabilise
Characterisation tests on the critical paths; CI and monitoring around the legacy system as it stands.
Stage by stage
Riskiest module first, behind a stable interface, verified against the pinned tests, shipped. Repeat.
Retire and document
Old components switched off only when their replacements have carried production load; documentation lands with each stage.
Pinned in tests, moved in stages, never stopped.
Proof, not claims
Modernisation claims are cheap; ours come with a dated anchor case and long-lived systems still running.
The anchor rewrite
A 14-year-old Go backend rewritten to Node.js in six months by one senior engineer using AI tooling — without prior Go expertise, against typical two-year quotes, with the system in service throughout. The method on this page is how.
A trading platform kept modern for years
Custom web trading systems — shares, futures, forex — where modernisation is continuous: real-time interfaces and integrations renewed without ever stopping the market clock.
A 14-year Go back end rewritten in six months
The legacy back end behind a live trading-education platform, rewritten from Go to Node.js in six months by senior engineers using AI-assisted workflows — with no interruption to the platform its 8,000+ monthly active users were trading on.
New flows beside old banking systems
Digital onboarding built inside a retail bank — new customer-facing systems integrated against long-lived banking infrastructure, on the bank’s own release path.
A 14-year-old backend was rewritten in 6 months against two-year quotes — one senior engineer, AI tooling, and tests pinning every behaviour that mattered.
Some components should be modernised; some should be left alone. An assessment that never says the second is a sales document.
Start with the estate assessment
The first engagement is the assessment: your legacy estate read by senior engineers, with a written verdict per component — modernise, stabilise, or leave alone — and a staged plan with dates for the parts worth moving. Priced in writing before it starts.
The 30-minute session is enough to size the assessment and often enough to spot the first quick win. You keep the notes either way.
Clients also buy
Code & Developer Audit
An independent human audit of the code — and of the team or vendor that produced it. Fixed price, in writing.
Product Rescue
A stalled or vibe-coded build, made production-grade — we take over where a vendor or a prototype stopped.
DevOps & Cloud Engineering
CI/CD, infrastructure as code, observability and cloud spend that stops surprising you.
AI reads the old code fast; a senior architect signs every stage. Speed and safety, in that order of appearance.
The questions buyers actually ask
How do you guarantee behaviour stays identical?
By making it testable before anything moves: characterisation tests capture current behaviour — including the quirks — and every replacement stage must pass them. Identical behaviour becomes something we prove per stage, not promise per project.
Why not just rewrite the whole thing?
Because parallel rewrites fail at a famous rate: the green-field build chases a moving target and loses. Staged replacement modernises the living system behind stable interfaces — each stage shippable, reversible, and verified. When a component genuinely warrants full rewrite, the assessment says so with numbers.
Where does AI actually help with legacy code?
Reading and translating it: AI tooling digests decades-old codebases and drafts translations at a pace humans cannot match — that is the 6-months-vs-2-years delta in our anchor case. Every drafted module then passes senior review and the pinned tests. The judgment stays human; the reading gets fast.
Our stack is obscure — can you handle it?
The anchor case was Go without prior Go expertise; the method is stack-agnostic by design: pin behaviour, read deeply with AI assistance, replace behind interfaces. We read and write JS/TS, Python, PHP and C++ natively, and have modernised across and out of stacks beyond those.
Can the business keep running during modernization?
That is a requirement of the method, not a stretch goal: stages ship behind stable interfaces while the system serves production, and old components retire only after their replacements have carried real load. The trading-platform work never stopped the market clock.
What does modernization cost?
The assessment is fixed-price and quoted before it starts; the staged plan it produces carries a per-stage price and date, so you approve spend stage by stage instead of underwriting a two-year bet on day one.
Team, scale and run — the one-page version
The seven Teams & Scale services on one printable page: what each covers, when it is the right door, and how the first month works. Built to be forwarded to whoever holds the budget.
Unfreeze the system, keep the business
Book the free 30-minute session for an honest read on your legacy estate — or describe the system in two sentences and an engineer replies in one business day.
- 30 minutes, an engineer on the call
- You keep the written notes either way
- Nobody follows up more than once
