Knowledge locked in old code
Business rules exist only in the legacy code, undocumented, and nobody is sure what will break if something changes.
Custom Software · Modernization
We modernize the old systems your business still depends on. We replace them piece by piece, move them to supported platforms or refactor them in place, so operations continue while the risk comes down.
Legacy software modernization is the process of moving a business-critical system that has become hard to change, support or secure onto a modern, maintainable foundation. Approaches range from re-platforming (moving to new infrastructure or a supported runtime), through refactoring (improving the code in place), to incremental rewriting, where new components gradually replace old ones. The right approach depends on how much of the existing system's logic is still valuable and how much risk the business can tolerate.
Legacy systems persist because they work and the business depends on them. But the original developers have left, the framework is unsupported, security patches no longer arrive, and every change takes longer than the last. The tempting response, a complete rewrite with a single switch-over date, is also the riskiest: it takes longer than planned, misses rules hidden in the old code, and freezes improvements while it runs. Incremental modernization trades a dramatic launch for steady, reversible progress.
Business rules exist only in the legacy code, undocumented, and nobody is sure what will break if something changes.
End-of-life languages, frameworks, databases or operating systems that no longer receive security updates.
No automated tests, tangled dependencies and manual deployment make small improvements expensive.
Replacing everything at once means a long period with no new value and a high-stakes cut-over at the end.
Code, architecture, data and infrastructure review covering risks, dependencies, hidden business rules and the parts of the system that matter most.
A recommendation between re-hosting, re-platforming, refactoring, incremental rewrite and replacement with a packaged product, per component, not one-size-fits-all.
New services built around the old system, with traffic routed to them feature by feature until the legacy component can be retired.
Moving applications to supported runtimes, current database versions, containers or cloud hosting with minimal code changes.
Tests that capture what the system does today, so its code can be restructured safely without changing behavior.
Schema redesign, data cleansing and migration scripts, with synchronization between old and new systems during the transition.
Each migration step is small and reversible, so problems are contained.
Modernized features reach users throughout the project, not only at the end.
Moving off end-of-life software restores access to security updates.
Tests, documentation and automated deployment make future improvements cheaper.
A Windows desktop system replaced with a browser-based application that staff can use from any location.
Applications on unsupported PHP or framework versions upgraded or rewritten module by module.
An in-house system gradually replaced with Odoo plus custom components, migrating one department at a time.
Applications containerized and moved to cloud infrastructure, with improved backups and deployment along the way.
The legacy system keeps running throughout; each step is verified before the next begins.
Review code, data, infrastructure and usage; interview users and the people who maintain the system.
Capture business rules and write characterization tests against the current system.
Agree an approach per component and a sequence that delivers value early and limits risk.
Add version control, automated deployment, monitoring and backups to the legacy system if missing.
Introduce an API layer or routing point where new components can take over from old ones.
Move one feature or module at a time, verify it against the old behavior, then switch traffic.
Move data in stages with reconciliation, keeping systems in sync until each part is retired.
Decommission old components once nothing depends on them, and archive what must be retained.
| Criterion | Re-platform | Refactor | Incremental rewrite (strangler fig) | Big-bang rewrite |
|---|---|---|---|---|
| Code change | Minimal | Moderate, in place | High, gradual | Complete |
| Risk | Low | Low to moderate | Moderate, spread out | High, concentrated at cut-over |
| Value delivered | Supportability and hosting | Maintainability | New features throughout | Only at the end |
| Best fit | Sound code on outdated infrastructure | Valuable code that is hard to change | Systems that need new architecture | Small systems or when the old one cannot run in parallel |
Unsupported components are identified early and prioritized for upgrade or isolation.
Migration runs use access-controlled environments, and sensitive data is handled according to agreed rules.
Characterization tests confirm that modernized components produce the same results as the old ones.
Re-platformed systems can scale with containers and managed databases instead of single aging servers.
We favor strangler-fig and phased approaches over all-at-once rewrites, and explain when a rewrite is truly justified.
Business rules are extracted and tested before they are reimplemented, so nothing is quietly lost.
If Odoo or another product can replace part of the legacy system, we include that in the strategy.
Version control, CI/CD and monitoring are introduced as part of modernization, not left for later.
Fixed-price packages with the scope written down, paid stage by stage. Your project goes live once it's fully paid.
Official documentation and guidance if you want to read more about this topic.
Usually not all at once. A complete rewrite with one cut-over date carries the most risk and delays value; incremental replacement or refactoring is safer for most business-critical systems. A full rewrite can make sense for small systems or when the old platform simply cannot be extended.
It is a way to replace a legacy system gradually by building new components around it and routing functionality to them one piece at a time. When nothing depends on the old component any more, it is retired, so the system is never switched off in one go.
We extract rules from the code and from interviews with users, document them, and write characterization tests that record how the current system behaves. New components must pass the same tests before they take over.
Yes. Incremental approaches are designed so the legacy system stays in use while parts of it are replaced, with data kept in sync between old and new components during the transition.
It depends on the size of the system, the quality of its code and data, and the approach chosen. Because incremental modernization delivers in stages, you see results well before the whole program finishes; we propose a sequence after the assessment.
The main factors are the size and complexity of the codebase, how well the business rules are understood, data volume and quality, the number of integrations and the chosen strategy. An assessment phase gives the basis for a realistic estimate.
Next step
Tell us what the system does, what it runs on and what worries you about it. We'll suggest where modernization should start.