A working legacy system is an asset, not a problem. The problem is that nobody dares touch it any more. We put it under test, lift it out piece by piece, and retire each old part only once the new one has proved itself.
A legacy system is rarely broken. It works — which is exactly why nobody touches it. The cost does not come from downtime but from what never gets done: every new feature becomes a negotiation with code nobody fully understands any more, every integration needs its own exception, and every person who knew the system takes part of that knowledge with them when they leave.
Modernisation does not mean rewriting everything. It is a series of decisions about what deserves to be kept, what deserves to be rebuilt, and what should simply be switched off. Most of those decisions are made before the first line of code — in an audit that establishes where the business logic actually lives and what is keeping it running.
Modernisation runs in three parts: first establish what you actually have, then rebuild what warrants it, and only then move. None of them requires the system to stop in the meantime.
We start from the code, the database and the infrastructure. We map where the business logic sits, which parts are business-critical, which dependencies have fallen out of support, and where the security gaps are. The output is a written assessment with priorities rather than an estimate based on a feeling.
We restructure the application so that technical debt goes down and the business logic survives. A monolith is broken into manageable parts where that pays for itself, not because it is fashionable. Before any change we write tests that pin down current behaviour.
Moving databases, operating systems and applications onto current platforms — AWS, Azure, Google Cloud, or your own servers inside the EU. The migration is rehearsed against a copy of production data, and the real cutover happens only after clean rehearsals.
A legacy system that talks to none of today’s tools is an island. We put an API layer in front of it that makes the existing logic reachable without having to replace what sits underneath straight away.
In old systems the data usually exists but cannot be reached. We surface it in a form that can actually be used, without a report requiring somebody’s manual work every Monday.
The biggest risk in an old system is not the code but that nothing about it is written down. Every modernisation phase ends with documentation that lets the next person continue without doing archaeology first.
In a modernisation the target platform is always a trade-off between what is newest and what you will still be able to hire for in five years. We pick the second.
The case for modernising is not that a system is old. These four are measurable before and after, and they are the only reasons worth starting a programme for.
The cost of a legacy system is not the licence fee. It is the time spent keeping it alive.
An old application was not built to current security standards, and the patches added over the years are often a new attack surface in themselves.
Most of the gain comes not from new features but from removing the steps somebody currently does by hand.
The most expensive thing about a legacy system is what you cannot do with it, and a competitor can.
Most modernisation programmes that fail began before anybody had the full picture. So ask first what happens before development: whether there is an audit, whether each application is tied to a defined business outcome, and whether you get a phased roadmap — with the reasoning for that order — before any code is written.
Ask as well how old and new run side by side in the meantime, because that is where most programmes get expensive. And ask who owns the repositories, the cloud accounts and the documentation. A modernisation that swaps one dependency for another is not a modernisation.
We don’t price the rebuild of a legacy system before we have seen the code. The audit can be bought on its own, and its output is yours even if you continue with somebody else.
Characterisation tests pin down current behaviour, bugs included, before anything moves. That makes it clear later which changes were intentional.
Capabilities move one at a time and the old system keeps running alongside. Every step is reversible until the last moment.
The engineer who did the audit is the one who does the rebuild. There is no handover between teams, because knowledge of an old system never writes down completely.
Repositories, cloud, domains. The point of modernising is to get out of a dependency, not to relocate it.
We are in Tallinn, in the same timezone and the same contractual framework. Data can stay entirely inside the EU.
No, and we almost never recommend it. We use the strangler pattern: the new system takes over one capability at a time, the old one keeps running alongside, and each part is retired only once its replacement has proved itself in production.
That’s the rule rather than the exception. We start from a code and database audit and write characterisation tests that pin down current behaviour, bugs included. That makes it clear later which behaviour was intentional.
The migration is rehearsed against a copy of production data as many times as it takes, and every run has a written rollback plan. The real cutover happens only after at least two consecutive clean rehearsals.
The signals usually arrive together. Your developers spend most of their time keeping the existing system running rather than building anything new. Every integration with a current service needs a workaround. IT spend rises without a matching rise in output. And experienced people don’t want to work on that codebase, which makes hiring expensive too.
The industry works with seven: rehost, replatform, refactor, rearchitect, replace, retire and retain. That last one is the correct answer more often than suppliers admit.
The choice is made per application, scoring each on six axes: business fit, business value, agility, cost, complexity and risk. Applications that score badly on several axes at once are the clear candidates. A real programme almost always combines several approaches at the same time.
It depends entirely on how many applications are involved and how deep the work goes. A straightforward move to a new platform is a matter of weeks. Rearchitecting a business-critical system with a data migration behind it is months, and in a larger organisation it can be years.
That is why we don’t give a timeline before the audit. The audit’s output is a phased roadmap where each phase has its own scope and its own business outcome, so you never have to approve the whole programme at once.
Not when the programme is built properly. Old and new run side by side throughout delivery and capabilities move one at a time — the aim is continuity, not a single hard cutover that either works or doesn’t.
The practical protection against that risk is a thorough discovery phase before development: dependencies, data risks and integration points have to be understood before anything moves. If somebody offers modernisation without that phase, it’s a risk rather than a saving.
An old application was not built to current security standards, and the patches and workarounds added over the years are often a new attack surface rather than a closed one. Unsupported versions stop receiving security fixes, which means a known vulnerability simply stays open.
In regulated sectors — finance, healthcare, insurance — compliance risk stacks on top of that: requirements change, and a system that cannot be changed cannot move with them.
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