RebuildEnterprise application modernization
We move client-server applications and aging Java or .NET systems onto modern architectures on AWS, Azure, Google Cloud or Oracle Cloud. One system at a time, with the business running throughout.
Legacy systems rarely fail all at once. They get slower, riskier and more expensive every year.
A minor fix touches several parts of the system, so every release feels risky.
The people who understand the system are retiring, and their skills are hard to hire.
Modern apps, APIs, data platforms and AI can't plug into the old system.
Licenses, hardware and unsupported versions cost more every year, and so do security gaps.
Performance drops as users and data grow, and scaling means buying bigger machines.
In most environments, the problem isn't a lack of effort. It's a lack of engineering structure that built up over years.
Boundaries were never defined, so one small change ripples across the system.
Systems rely on databases, files and interfaces with no clear contracts.
The architecture was designed for the first release, not for today's volume.
Documentation, release discipline and module ownership have faded over time.
Because failures hit daily operations, teams avoid touching the system at all.
Modernization isn't one strategy applied everywhere. We choose per system, based on business value, risk and budget.
Move the application to the cloud largely as it is.
Fits when speed matters most, such as a data-center exit or expiring hardware.
Upgrade the runtime, database or infrastructure with minimal code change.
Fits when the code is sound but the platform underneath is outdated or unsupported.
Restructure the code to be cleaner, faster and easier to change.
Fits when the system does the right things but is too hard to maintain.
Redesign into modular, API-first or cloud-native services.
Fits when the business needs have outgrown what the design can support.
Some systems are best left as they are, or retired. The Blueprint tells you which, and we'll say so.
The legacy estates we work with most, and where they typically land.
We rehost, replatform and rearchitect onto AWS, Azure, Google Cloud or Oracle Cloud Infrastructure, and set the new environment up with monitoring and tested recovery from day one.
Accounts, networking and access designed before the first workload moves.
Every environment defined in code, so environments don't depend on manual setup.
Baselines for identity, encryption, logging and audit from the start.
Observability, alerting and tested recovery for every migrated system.
Right-sized resources and spend tracking, so cloud spend is tracked and kept in check against the data center it replaced.
The riskiest part of modernization is the period when old and new run side by side. We plan that period as carefully as the build.
Inventory, dependencies and AI-assisted code analysis.
You get a roadmap with the right path, risk and cost for each system.
Sequence low-risk systems first and design temporary bridges.
You get a cutover plan with rollback criteria for every step.
Replace one capability at a time while the old system keeps running.
You get working, tested slices you can review every two weeks.
Parallel runs, data reconciliation and a rollback ready to go.
You get sign-off only when numbers match and users are ready.
Monitoring, documentation and continued improvement.
You get a maintainable system and a team that knows it.
Decades of undocumented logic is the hardest part of modernization. AI helps us read it faster. Engineers decide what to keep, change or retire.
Trace dependencies between programs, databases and interfaces, including the ones nobody wrote down.
Turn undocumented code into plain-language descriptions your team can review.
Generate tests that capture what the system does today, before anything changes.
Accelerate repetitive conversion work, with every change reviewed by an engineer.
Our commitments on every modernization program.
No big-bang switchover. We plan every step so the business keeps running.
Every migration is reconciled, so the new system's numbers match before the old one is switched off.
Rollback criteria are agreed before each cutover, not after something goes wrong.
Connected systems keep working, through temporary bridges where needed.
What we learn about the old system is documented, so it no longer lives in one person's head.
Your engineers work alongside ours and own the new system confidently when we're done.
Continuity is what we're known for.
Enterprise partnership, healthcare
A dedicated Vanna team inside the client's engineering organization since 2019, across platform engineering, integrations, quality and support. Priorities changed; the core team didn't.
Read the story“They modernized a legacy application without disrupting business operations. The system became easier to maintain and our release cycles improved.”
Further reading
Modernizing without breaking: a phased approach to legacy systems Why application modernization fails without an operating modelMost programs begin with a Modernization Blueprint, so decisions are based on facts rather than guesses.
The best first step
We map your systems, dependencies and risks, and recommend a path for each one.
For multi-system programs
A dedicated team that delivers the roadmap slice by slice, alongside your engineers.
For systems you need to keep running
We take over support of the legacy system and modernize it gradually from the inside.
No. Cloud is often the right target, but not always. The Blueprint weighs cost, risk and your constraints, and some systems are best kept on-premises or left as they are.
We avoid big-bang cutovers. New and old systems run side by side, each slice is switched over only after parallel runs, and rollback criteria are agreed in advance.
Yes, that's common. AI-assisted analysis and working sessions with your team help us map what the system actually does, and we document it as we go.
The Modernization Blueprint takes about three to four weeks and gives you a timeline for each phase. A program depends on the number and size of systems. Because we work in slices, you typically see results within the first few months, not at the end.
Every migration includes reconciliation, so we prove the new system's numbers match before the old one is switched off. See our data engineering and migration practice for more.
Yes, and we recommend it. Your engineers work alongside ours, so they own the modern system with confidence afterwards.
Yes. Starting with one high-value, lower-risk capability is often the best way to prove the approach and build confidence.
About three to four weeks, fixed scope, ending with a clear roadmap you can act on.