Replace it in pieces, not in one leap.

The big rewrite is
the riskiest plan available.

Every route, integration, scheduled job and undocumented behaviour, established from the code and from real traffic rather than from a diagram nobody updated.

Which slice moves first and why, with each step delivering value on its own so the programme survives a change of priorities.

A boundary between old and new so the legacy data model stops propagating into everything you build next.

Dual writes or change capture, reconciliation reports, and a period where both systems agree before anything is switched off.

APIs and integrations kept working, so downstream consumers and partners are not dragged into your migration.

What gets switched off, when, and how you prove nothing still depends on it. Most modernisations quietly keep paying for the old system.

Every change carries unknown risk, so changes stop happening and the backlog becomes a list of things nobody will attempt.

A framework, runtime or database version is losing support, which turns modernisation from a choice into a deadline.

The stack narrows your candidate pool, and the people who understand it are the ones you cannot afford to lose.

A system deployed separately per client, where every change is multiplied by the number of installations.

Audit trails, access control or data residency are impossible in the current architecture rather than merely missing.

The infrastructure bill grows faster than usage, and the architecture is the reason rather than the traffic.

Understanding the old systemused to be half the budget.

Months of reading, done in weeks

Legacy code analysed to extract business rules, branch conditions and data flows into documentation your team can review. This is normally the single largest unknown in a modernisation estimate.

Behaviour captured before it changes

Characterisation tests generated against the existing system from real inputs and outputs, so the new implementation is provably equivalent rather than hopefully so.

Translation at scale, consistently

Repetitive translation and transformation across hundreds of files applied uniformly, where doing it by hand invites inconsistency and fatigue over months.

Extracted rules are confirmed against production behaviour.

A rule read out of old code is a hypothesis until it is verified against real traffic and with the people who know the business. Nothing is reimplemented on the basis that a model said the code appeared to do it.

When we would
leave it alone

A stable system with no roadmap and no compliance pressure is not a problem. Modernising it spends budget to arrive in the same place.

Often the complaint resolves to a slow report, a missing integration and an awkward screen. Fix those directly.

Where an off-the-shelf platform does eighty per cent of what your bespoke system does, buying beats rebuilding.

Modernisation needs the people who understand the current rules. Without their time, you are rebuilding from guesswork.

Share of real requests served by new code. The only honest measure of progress, and it cannot be fudged.

Disagreements between old and new during parallel running. Has to reach near zero before any cutover.

How long a change takes now versus at the start. The whole point is making the system cheap to change again.

Infrastructure and licence spend on the old system. If it is not falling, decommissioning is being skipped.

Tracked separately from ordinary incidents, so the risk of the programme is visible rather than absorbed.

Old paths actually switched off, not merely bypassed. Bypassed code keeps costing money and confusing people.

What modernisation
runs alongside