Legacy software modernisation doesn’t have to mean throwing everything away and starting again. At Bulb, it usually means we can help you in one of three ways… We adopt and maintain a system that already works, we adopt and build carefully on top of your existing product or we use our suite of efficient tools and process to help you cost-effectively take the best of your existing legacy product and develop it into something fit for your contemporary needs.
Most businesses we meet aren’t looking to rip out a system that still runs their operations. They generally want it to keep working and improve what it does for them – removing workarounds, idiosyncrasies and inefficiency and building value. Where it makes sense, they want it to do more than it currently does.
This is a very a different brief from building something new and one that we relish at Bulb Studios – good legacy software modernisation is just as rewarding as launching something new for a client.
The three shapes legacy software modernisation can take
Not every legacy system needs the same approach, so we usually start by working out which of three routes fits:
- Adopt and maintain. The software works and it’s business critical but nobody currently owns it properly. We are happy to examine, adopt and take over support; patching known issues and keeping it stable and secure.
- Adopt & build on top. The core system is sound but it’s missing capability the business now needs. We will follow the same adoption process but create a roadmap for careful extension; adding new features without breaking what already works.
- Redevelop and optimise. The system has reached a real limit, technically or commercially or over time has become inefficient. A proper rebuild is the sensible investment. We carry across what still has value and build it into a product fit for what your business needs now.
We work across all three approaches to legacy software modernisation. That means we can give an honest recommendation to suit your requirements and your budget.
When software becomes esoteric: diagnosing it properly
Some systems age quietly. Others become esoteric and only understood or usable by a select few who have become used to its foibles. Nobody on the team recognises the stack, undocumented workarounds hold it together, it only works if you know the right sequence… This is often where the real risk sits for business owners when nobody understands the system well enough to touch it safely.
This is where we can help. We examine the system first; we map what it does and where the real risk sits, then we diagnose the problems.
We don’t just assume a full rebuild is the only safe option. Quite often, when properly investigated and understood, a system that looks super-complex from the outside just needs a handful of targeted fixes.
How AI makes legacy software modernisation more affordable
Understanding an unfamiliar codebase used to be slow and expensive. AI has changed that. Our custom suite of AI-powered tools can scan and map an existing codebase fast. With these tools, we can flag risky or outdated dependencies and highlight hidden behaviour far faster than a manual audit ever could. As a result, a stage that used to need weeks of budget can usually be done in a matter of days.
Our post on AI and human creativity in digital product design covers how we pair AI with human judgement across all our work. Legacy software modernisation is one of the clearest places this is put into practice. For instance, AI handles the mechanical groundwork: scanning, mapping, flagging and our developers make the judgement calls about what’s safe to change, what needs rethinking and where there are opportunities for significant improvement. The result is a budget-friendly route into modernisation which, even a couple of years ago, wasn’t realistic for many businesses.
It’s important to note that the cost of doing nothing isn’t zero either though. Outside research on technical debt suggests it can quietly eat up a large share of a company’s technology spend. That’s because legacy systems tend to demand a steady stream of maintenance hours long after they were first built. Modernising sooner, with AI keeping the diagnosis affordable, is now often far cheaper than patching a system that’s slowly becoming harder to support.
Getting started with legacy software modernisation
If you’re not sure which path fits, that’s a great place to start. Our post on how to brief a digital product studio covers what’s useful to bring to that first chat. For legacy software, ‘we’re not sure what this system still does and how it works’ is a valid starting point.
Get in touch if you’ve got a system that’s ageing, awkward or overdue an independent assessment. If it’s still fixable, we’ll say so. If it needs a rebuild, we’ll help you do that affordably.
Photo by Brett Jordan on Unsplash
Frequently asked questions
Legacy software modernisation covers three routes: adopting and maintaining an existing system, building new capability on top of it or redeveloping it fully. The right approach depends on the system's condition and the business' needs.
Not necessarily. Many systems only need targeted fixes, better maintenance or careful extension. However, a proper diagnosis usually shows a full rebuild isn't always the best option.
AI tools can scan a codebase and flag outdated dependencies fast. They surface undocumented behaviour far faster than a manual audit. That cuts the diagnosis stage from weeks to days and makes modernisation more affordable.
That's a common and solvable problem. We examine and diagnose esoteric or undocumented systems before recommending any changes. So decisions are based on real understanding, not guesswork.
It depends on the system's condition. Ongoing patching can cost more over time than a well-scoped modernisation project. In fact, AI-assisted diagnosis helps by bringing the upfront cost of assessment down.
Yes, where the core system is sound. In fact, extending an existing system is often faster and less disruptive than a full rebuild. It's one of the three approaches we regularly recommend.
We examine what the system does and how it does it. We work out where the real risk sits. Then we recommend adopting, extending or redeveloping it, based on that diagnosis rather than a fixed playbook.
