Software & Product Engineering
Application Modernisation
Move ageing applications onto modern, supportable platforms step by step — keeping the business running while you cut technical debt, run costs and dependence on scarce skills.
Is this for you?
You might need this if…
Key business logic sits in a legacy system that only a handful of people, some near retirement, really understand.
Licence, hardware or mainframe costs keep rising while the system holds back new digital services.
Your cloud programme has stalled because the applications that matter most can’t simply be lifted and shifted.
Every change to the old system takes months, and nobody dares to touch the code without a full regression cycle.
What we deliver
What it covers
Portfolio assessment and rationalisation
We map your applications by business value, technical health, cost and risk, and recommend for each whether to retain, retire, replace, re-platform or refactor. You get a modernisation plan focused where it pays off.
Re-platforming and refactoring to cloud
We move applications to cloud platforms such as Azure or AWS, from re-platforming onto managed services to refactoring code for cloud-native operation. You get lower run costs and easier scaling, without rewriting more than necessary.
AI-accelerated code conversion and documentation
We use AI to analyse legacy code, document what it does and help convert it to modern languages, always verified by experienced engineers and automated tests. Hidden business rules become visible and conversion moves faster.
Mainframe and legacy modernisation
We modernise mainframe and other legacy environments, for example COBOL or older 4GL systems, through rehosting, conversion or gradual replacement. Business-critical processing keeps running throughout.
API enablement of legacy systems
We wrap legacy functions and data in secure, well-documented APIs. New digital services can use the old system’s capabilities now, while the core is modernised behind the scenes.
Our approach
How we work
01
Assess
Inventory and analysis of applications, code, data, integrations and run costs, with input from the people who know the systems best.
02
Plan
A modernisation strategy per application and a sequenced roadmap, with business case, risks and a test approach.
03
Modernise
Incremental migration or conversion, with automated testing and parallel running where needed to prove equivalence.
04
Decommission
Switch-over, retirement of the old platform and its costs, and handover of the modernised application to operations.
Best practices
What we bring to every engagement
Strangle, don’t big-bang
Replacing functionality piece by piece behind stable interfaces keeps risk low and value flowing.
Capture business rules before you change code
Undocumented rules buried in legacy code are the biggest risk in any modernisation, so we extract and confirm them first.
Prove equivalence with tests
Automated regression tests and side-by-side comparisons of outputs show that the new system behaves like the old one.
Not everything needs rewriting
Some applications are best retired, replaced by SaaS or simply re-hosted — the right answer differs per application.
Plan the data as carefully as the code
Data migration, cleansing and reconciliation often decide whether a modernisation succeeds.
Count the savings only when the old platform is switched off
Benefits arrive when legacy licences, hardware and contracts actually end, so decommissioning is part of the plan.
Outcomes
What you get
- A complete view of your application portfolio and its technical debt
- A modernisation decision for each application, with business case
- Documented business rules and legacy code
- Applications running on modern, supportable platforms
- APIs that open legacy data and functions to new services
- Retired legacy platforms and reduced run costs
AI-powered
Unleash the power of AI
We offer the possibility of using AI throughout this work: ready-to-use AI tools, or a customised version built for your organisation that can run inside your own infrastructure. In application modernisation, AI reads large legacy codebases, explains and documents what they do, extracts business rules and drafts converted code and test cases — work that engineers then review and verify, which shortens the slowest and riskiest phases of a migration.
Starter offer
Legacy Modernisation Assessment
A fixed-scope, five-week assessment of your legacy applications that gives you a modernisation decision per system and a sequenced, costed roadmap.
Week 1
Inventory
Collection of application, code, cost and integration data, and interviews with system owners.
Weeks 2–3
Analyse
Technical health, business value and risk assessed, with AI-assisted code analysis of the most critical systems.
Week 4
Decide
Modernisation options per application worked through with your team, including retire and replace options.
Week 5
Roadmap
Sequenced roadmap, business case and recommendations presented to management.
You receive
- An application portfolio map with health, value and cost
- A recommended modernisation route for each application
- Documentation of critical legacy code and dependencies
- A sequenced roadmap with business case and risks
FAQ
Frequently asked questions
How long does a modernisation take?
It depends heavily on the size and complexity of the systems: a single application can typically be re-platformed in a few months, while a mainframe exit is usually a multi-year programme run in stages. The assessment gives you a realistic estimate for your portfolio.
Can you modernise without disrupting daily operations?
Yes, that is the aim of an incremental approach. Old and new run side by side, functionality moves over in stages, and each step is tested against the existing system before switch-over.
How does Altechy work with our current supplier for the legacy system?
We work alongside your existing suppliers and in-house experts, whose knowledge of the system is valuable. Altechy brings the modernisation specialists from our partner network and stays your single point of contact for the overall programme.
Is AI-converted code safe to put into production?
Only after it has been reviewed by experienced engineers and passed automated and regression testing, like any other code. AI speeds up analysis and conversion, but accountability for quality stays with the team.
Related services
Cloud Strategy & Migration Custom Application Development Integration & APIs Quality Engineering & Testing Technology Strategy & Advisory Application Management & Support
Let’s modernise your legacy applications
Book a free 60-minute idea session. We explore your challenges and opportunities with you, and suggest where to start — with no obligation.