Your legacy system is not broken. It is just no longer hireable, supportable, or safe to change.
The platform still runs, but support has ended, the original engineers are gone, and you can no longer hire for the stack. At that point modernization is not a strategic choice. It is a maintenance threshold you have already crossed.
The reason you are reading this page
Most legacy modernization conversations do not start with strategy. They start with a specific trigger. Recognizing yours tells us where to begin.
Vendor support is ending and security patches are stopping.
Silverlight, .NET Framework 4.x, AngularJS, older Java runtimes, on-prem SQL Server versions. The platform is still running, but the patch pipeline is closed. Every quarter the system stays on the old stack is another quarter of unpatched vulnerabilities sitting in production.
You cannot hire engineers willing to work on this stack.
Job postings sit unfilled for six months. The candidates who do apply ask about modernization plans in the first interview. The engineers who do know the legacy stack are charging premium rates because the talent pool keeps shrinking.
Audit findings or compliance changes the system cannot absorb.
SOC 2, HIPAA, GDPR, PCI updates land. The existing architecture has no clean way to add the required controls. Every fix becomes a workaround layered on top of older workarounds, and the audit trail is starting to look like the problem.
Infrastructure spend is rising faster than the business.
The system was built when storage was expensive and compute was scarce. The architecture reflects those assumptions. Today, the spend is dominated by inefficiencies the original design never anticipated, and procurement is asking questions the engineering team cannot answer with the current setup.
Why most legacy modernizations run over budget and under scope
The technology is rarely the problem. Modernizations stall for three predictable reasons. Engineering leaders who have run a modernization before know all three. Engineering leaders running their first one rarely see them coming until it is too expensive to course-correct.
Scope drift mid-project.
The vendor quoted based on what you described. The codebase contains what was actually built. The gap surfaces during sprint three, when undoing decisions is expensive and morale is starting to dip.
The parallel run that never ends.
The rebuilt system goes live for some users. The legacy system stays running for others. Two years later, both systems are still in production, both need maintenance, and the cutover keeps slipping because no one is willing to own the risk of switching off the old one.
Domain knowledge that walks out the door.
Years of business rules live inside the codebase. Some were written by engineers who have left. Some have been changed so often the rules now contradict each other. Modernization has to extract that knowledge into the modern system, not lose it on the way.
Three phases. One outcome: a system your team can maintain, hire for, and ship from.
Every phase has a defined deliverable. No phase begins until the previous one is reviewed and signed off with your engineering leadership. You can pause, re-scope, or end the engagement at any phase boundary, and the structure is designed so that stopping early still leaves you with a usable result, not a stranded project.
Phase 1
Codebase assessment and migration plan
Automated code analysis maps dependencies, dead code, and risk concentration. Senior engineers validate the output. You get a written report covering effort estimates per migration path, hidden risks surfaced before contract, and a recommended sequence.
Phase 2
Parallel rebuild, sprint by sprint
Components are rebuilt in priority order on the modern stack. Business rules are extracted from the existing system and documented as they move. Each sprint produces a working slice running in parallel with the legacy system, reviewed end to end with your team.
Phase 3
Cutover with rollback windows and handoff
Staged cutover with defined rollback procedures at each step. AI-generated regression test suites verify behavior parity. Runbooks, architectural documentation, and knowledge transfer to your engineering team complete the engagement.
Three paths. The assessment tells us which one fits.
Not every system needs to be rebuilt from the ground up. Some need a lift to current cloud, some need a framework refresh, some need a full re-architecture. The assessment determines which path returns the most value per dollar of engineering effort.
Rehost to Cloud
Starting point: On-prem, supported framework
Move the existing system to managed cloud infrastructure without architectural changes. Reduces infrastructure spend, eliminates data centre obligations, and buys runway for a deeper modernization later.
Best when: the platform is still supported, but the data centre is no longer economical.
Replatform to Modern Framework
Starting point: End-of-life framework, working architecture
The application shape stays. The framework changes. Silverlight to Angular. .NET Framework 4.x to .NET 8. AngularJS to React or Angular 17. VB.NET to C#. Restores supportability, security patching, and a hiring market.
Best when: the system works, but the stack underneath it is on borrowed time.
Rearchitect to Services
Starting point: Monolith hitting a maintainability ceiling
Decompose the monolith into bounded services. API-first interfaces. Independent deployments. The maintainability ceiling lifts. Teams ship without coordinating around a single release train, and the system can absorb the next decade of product changes.
Best when: every change feels expensive, even small ones.
AI-assisted engineering is built into the method, not sold as a premium offering.
Every engineer on an AnAr modernization works AI-assisted from day one. This is how we work on every project. It compresses timelines, surfaces risks earlier, and produces documentation that does not get skipped under deadline pressure.
"We do not run a separate AI practice. Every engineer here uses AI-assisted development as standard practice, on every project. On a modernization engagement, that shows up as faster assessments, cleaner cutovers, and documentation your team will actually use."
On every engagement
What AI-assisted delivery looks like in practice
- Automated dependency mapping across the full codebase, including the parts no one has touched in years
- AI-assisted code analysis to identify dead code, redundant logic, and high-risk concentration
- AI-generated regression test suites covering existing behavior before any rewrite begins
- AI-drafted architectural documentation and runbooks, validated by senior engineers
- AI-assisted code review on every pull request, layered on human review
What this looks like in practice
Three engagements with the same shape as most of the systems on this page. Each client started where you are: a working application on a stack that had stopped supporting them.
NMLS-regulated mortgage-education portal rebuilt from .NET Web Forms to .NET Core and Angular
.NET Web Forms / MS SQL → .NET Core / Angular 11 / Azure
A US EdTech company's mortgage-education portal was a compliance-regulated .NET Web Forms codebase that could not scale with the business, and the talent to safely change it had become hard to find. AnAr took over the source and maintenance within weeks, built a modernization roadmap, and migrated to a cloud-native .NET Core and Angular stack, with a dedicated unit-testing methodology to protect NMLS compliance through every change.
99% system uptime, 30% fewer production support tickets, 100% improvement in page response time.
Silverlight fertility-treatment platform rebuilt on Angular 16 and .NET Core
Silverlight / .NET Framework / WCF → Angular 16 / .NET Core / AWS
A fertility-clinic SaaS provider was stranded on Silverlight after browser support ended. Their customers could no longer reach the platform. Hiring Silverlight engineers had become impossible. AnAr executed a phased rebuild: N-tier architecture for loose coupling, full Angular 16 frontend rewrite, gradual .NET Core 7 backend transition, AWS adoption.
Browser independence restored, market expansion unblocked, supportable stack ready for the next product roadmap cycle.
German manufacturer's Windows ERP re-engineered for global rollout
Legacy Windows ERP → Angular / .NET Core 6 / Azure DevOps / SAP integration
A German manufacturer's automotive-parts servicing system was unmaintainable, unable to scale, and could not be deployed across international offices. AnAr migrated to a cloud-native architecture, integrated with SAP ERP, added multilingual support for the global workforce, and built analytics for parts failure and repair metrics.
Scalable architecture deployed across international offices, SAP integration live, multilingual rollout complete, automated data onboarding running in production.
Modernizing because you want to ship AI features?
This page covers modernization driven by support, hiring, compliance, or infrastructure spend. If your real driver is shipping production AI on top of a modern foundation, the sibling engagement is structured differently. The assessment is codebase plus AI-readiness, and the build integrates AI capabilities as each component lands.
Why engineering teams choose AnAr for modernization
We start with your existing codebase, not a blank proposal.
The assessment gives you a real picture of effort and risk before you sign anything. No guesses. No discovery phase billed at consulting rates before the actual work starts.
Every engineer works AI-assisted, on every project.
AI-assisted code analysis, AI-generated test suites, and AI-drafted documentation are how we work, not a separate offering. This is what makes the timelines and quality possible.
150+ projects delivered. 95% client retention. The patterns repeat.
Silverlight to Angular. VB.NET to ASP.NET Core. On-prem Windows ERP to Azure. The patterns repeat across industries and team sizes, which is why we know where the surprises live before the work begins. Clients who complete one engagement return for the next.
Production cutovers, not pilots that never ship.
Staged cutover with defined rollback procedures. Regression test suites that verify parity before traffic moves. The work ends when your team owns the modernized system, not when the slide deck is reviewed. We do not take modernization engagements we cannot define in milestones. If your situation calls for open-ended consulting, we will say so before contract and point you elsewhere.
Know what you are committing to before you commit.
Share the basics of your system. AnAr's engineers, supported by our automated code analysis, produce a written report covering the dependencies you cannot see, the risks the documentation does not mention, and a realistic effort estimate for each viable migration path. The report is yours regardless of whether you continue with us. You only commit to an engagement once you have reviewed the findings.
What the assessment maps:
- Dependency structure and integration points across the full system
- Technical debt concentration, where the real risk lives, not just where it looks risky
- Dead code, redundant logic, and cleanup candidates
- Security vulnerabilities and compliance gaps
- Migration path options with estimated effort per path
- Recommended sequence with milestone-level breakdown
Your source code is your IP. Confidentiality terms are agreed in writing before any code is shared, and visibility is limited to the assessment engineers assigned to your engagement. The assessment itself is not a paid engagement. You only commit once you have the report.
Request a Modernization Assessment
A few details so the right engineer can review your system and follow up.
What engineering leaders ask before starting a modernization
If your question is not covered below, the modernization assessment is the fastest way to get a specific answer. Most general questions are addressed here.
How long does a legacy modernization engagement typically take?
Three to four months for a focused replatform of a single critical module. Six to nine months for a framework refresh across a mid-sized application. Eighteen months to multiple years for a full monolith-to-services rearchitecture on an enterprise-scale system, executed in parallel workstreams with quarterly review gates. Those are the ranges across our recent portfolio, not promises for your system.
The codebase assessment in Phase 1 produces a precise estimate for your specific system before you commit to anything beyond the assessment itself. We size by component count, dependency depth, and integration surface, not by rough vendor heuristics.
How is the engagement priced? Fixed bid, time and materials, or milestone-based?
We work in fixed-scope milestones derived from the codebase assessment, not open-ended time-and-materials. Each milestone has a defined deliverable, a price agreed up front, and a review gate. You approve milestone completion before the next milestone starts.
This shifts risk away from your team: scope drift inside a milestone is our problem to manage, not your budget's. For longer engagements, we deliver in quarterly increments with explicit stop points built in so the engagement can be paused, re-scoped, or ended at any quarter boundary without penalty.
What if our original engineers have left and the documentation is incomplete?
Yes, and this is the situation in roughly half the legacy systems we assess. It is not a blocker, and it is rarely as bad as the engineering team fears. Our automated code analysis maps the system as it actually behaves at runtime, not as it was once documented. Control flow, data flow, integration points, and conditional logic are extracted directly from the source.
Business rules are extracted from the running code path, validated against production behavior, and confirmed with your remaining team during Phase 1. The output of the assessment is, in many cases, the most accurate documentation your system has had in years. That documentation alone is often valuable independent of the modernization itself.
How do you handle the parallel-run and cutover risk?
Cutover is staged, not big-bang. We define rollback procedures for every cutover step before execution. AI-generated regression test suites built during Phase 2 verify behavior parity between the legacy and the rebuilt system under representative load.
The legacy system is not switched off until the rebuilt system has matched it under live traffic for an agreed observation period. The parallel-run window has a defined end date and a defined acceptance criterion, both written into the engagement plan. If acceptance criteria are not met, the rollback is executed and the migration is re-sequenced, not forced through.
Will our engineering team be able to maintain the modernized system after handoff?
Yes. Knowledge transfer and handoff are deliverables of Phase 3, not optional extras. Your engineering team receives architectural documentation, AI-drafted and engineer-validated runbooks, deployment guides, and a working CI/CD pipeline.
Pair-programming and shadow-deployment sessions are scheduled in the weeks before the engagement closes, so your team operates the system under our supervision before they operate it alone. The work is not finished when the system is live. The work is finished when your team can ship, deploy, and operate the system without us in the room.
How do you protect our source code during the assessment and engagement?
Confidentiality terms are agreed in writing before any code is shared. Codebase visibility is limited to the assessment engineers and the migration team assigned to your engagement. Your source code remains your IP throughout. We operate from secured environments with audit logging, and engineer-level visibility is revoked at engagement close.
If your security policy requires on-premise execution of analysis tooling, dedicated VPN connectivity, or self-hosted code repositories, we accommodate that during scoping. We have run engagements under HIPAA, SOC 2, and EU GDPR constraints. The handling pattern is sized to your compliance environment, not the other way around.
We are on .NET Framework 4.x, VB.NET, Silverlight, AngularJS, or older Java. Do you handle our stack?
Yes. Recurring migration paths in our portfolio include:
.NET Framework 4.x to .NET 8 or later. VB.NET to C# on ASP.NET Core. Silverlight to Angular 16 or later. AngularJS to React or modern Angular. On-prem Windows ERP to Azure or AWS. Older Spring or J2EE to Spring Boot. Monolithic PHP to service-oriented PHP or Node. Classic ASP to .NET Core. MS Access or FoxPro backends to modern relational databases.
The patterns repeat. We know where the difficult parts of each migration live before the work begins. That recurring knowledge is what makes the assessment timeline compressed and the estimates trustworthy.
How is data migration handled when the database schema needs to change?
Data migration is sized and planned in Phase 1 alongside code migration. We do not separate them, because schema changes that are safe in isolation often break behavior when paired with rebuilt business logic.
Data is migrated in dual-write mode during the parallel-run period, with reconciliation jobs verifying integrity between the legacy and the rebuilt data stores. Schema evolution is handled via versioned migrations, not one-shot scripts, so that rollback is possible at any point during cutover. Sensitive fields are masked or tokenized during non-production movement where the compliance environment requires it.
How do you keep our integrations from breaking during the migration?
Integration mapping is part of Phase 1. We identify every upstream and downstream system the legacy application connects to: ERPs, payment gateways, identity providers, partner APIs, file drops, scheduled batch jobs, webhook receivers, and email or SMS providers.
The modernized system either preserves the existing contract or introduces a versioned interface with a deprecation timeline communicated to integration owners. We do not break integrations silently. We do not assume integrations are the customer's problem after handoff. If an integration owner cannot move to a versioned contract within the engagement window, the legacy contract is kept live through a translation layer until they can.
Do you provide ongoing support after the modernization engagement closes?
Yes. Two common patterns.
First, a defined hyper-care window immediately after cutover, typically thirty to ninety days, with our engineers on shared channels for production support. This is included in most modernization engagements at no incremental price.
Second, an ongoing application maintenance retainer for clients who want us engaged for continuing feature work, security patching, and operational support. Both are optional. The base engagement is structured so that your team can take full ownership at handoff if that is the preference.
Can we start with a single module rather than committing to the full modernization?
Yes, and we often recommend it. A scoped first engagement on the highest-risk or highest-value module proves the working relationship before larger commitment. Modules suitable for a first engagement are identified during the assessment based on isolation potential, business criticality, and migration effort.
The architectural choices made for the first module are designed to extend, not to be redone, when the next module is taken on. The engagement is structured so that stopping after the first module produces a usable, supported result, not a partial migration that leaves you worse off than before.
What is the difference between this engagement and AnAr's AI-Driven Application Modernization engagement?
Different buyer trigger, different engagement shape, same engineering team.
The Legacy Application Modernization engagement (this page) is driven by support sunsets, hiring scarcity, compliance findings, or infrastructure spend. The output is a modernized system on a supported stack with a hireable talent pool. AI-assisted engineering shows up as the method we use to deliver, not the product.
The AI-Driven Application Modernization engagement is driven by a desire to ship production AI features, and the modernization is structured around AI readiness from day one: API-first architecture, structured data pipelines, and AI capability integration delivered alongside the architectural work. If your real driver is AI readiness, that engagement is the right starting point.
What if the assessment recommends not modernizing?
It happens, and we say so. Sometimes the right answer is a targeted refactor of one component rather than a full modernization. Sometimes it is keeping the legacy system on extended support for another budget cycle while focusing engineering effort elsewhere. Sometimes it is a pure cloud rehost without architectural changes.
The assessment recommends what the system needs, not what is profitable to recommend. If the assessment finds that modernization is not the right next move, you have a written rationale to take to your board, and you have spent nothing beyond the assessment.
Two to four weeks from now, you could have an answer instead of a hypothesis.
Request a modernization assessment
A written assessment of your system. A recommended migration path. A milestone-level price. Then you decide what happens next.
Request a Modernization AssessmentModernizing because you want to ship AI features? See AI-Driven Application Modernization →