Route manifest
One line per page decides which app answers it. Patterns are supported, so a whole template family flips as one group instead of page by page.
Every release on an aging stack is a risk, and fewer engineers want to work on it. We move .NET Framework to .NET 8, Java 8 monoliths to Java 21, AngularJS and WebForms to React and VB6, Delphi and WinForms systems forward in packages that ship one at a time, while the old system keeps serving everything not migrated yet.
Two apps run in parallel behind one domain. Migrated routes are served as real pre-rendered pages; everything else hits a catch-all that proxies the request unchanged to the legacy app. Same domain, no redirects, cookies intact.
One line per page decides which app answers it. Patterns are supported, so a whole template family flips as one group instead of page by page.
Checks the manifest on every request: migrated pages are served by the new app, everything else is proxied to the legacy one. Optionally driven by an environment variable, so a flip needs no deploy at all.
The user token moves into a domain-scoped cookie both apps read, so a login on either side is valid on both. Temporary bridges keep shared state, such as a cart, in exactly the format the legacy app expects, and are deleted once that flow migrates.
Framework-free pricing, discount and calculation code becomes a shared package imported by the new app and loaded by the legacy one exactly as before. One source of truth, covered by a parity test suite that proves both produce identical results.
"/pricing" : "next" // migrated, served by the new stack "/catalog/*" : "next" // a whole template family, flipped as one group "/checkout" : "legacy" // still served by the old app, untouched
Flipping a page is one line and a deploy, roughly two minutes. Rolling it back is the same line reversed.
Both routes end at the same modern stack. They differ in what happens between the decision and the finish line.
Everything after it runs on this machinery, and it produces the plan and the estimates for the next packages from your actual code rather than from assumptions.
A solution architect goes through the codebase with your developer in a walkthrough session, then writes the plan and the estimates for the following milestones.
New project and CI, front-door routing with per-page switching in both directions, deployment pipeline, domains and SSL, rollback path, shared login session across both apps.
Business logic extracted into a shared package, a test suite proving identical results, and one real page switched live in production, then switched back to prove the rollback path.
Work is contracted in short packages of one to three weeks. A larger milestone spans several of them.
Three things are decided after the foundation stage rather than guessed now: whether flips go through a deploy or an environment variable with no deploy at all, how the most complex module is split between our engineers and yours, and the estimates for the remaining milestones, planned out during the audit from your actual codebase.
Blanket discounts on AI do not survive contact with a real migration. Measured reality is uneven: overall project gains land around 10 to 30 percent even with near-universal tool adoption, while specific task types genuinely run twice as fast.
| Work type | AI impact | What the human keeps |
|---|---|---|
| Type definitions, scaffolding, configuration | 60–80% faster | Correctness review |
| Converting framework-free business logic | 70–90% faster | Parity test sign-off |
| Simple and static pages | 50–60% faster | Visual QA |
| Template sections and UI components | 40–50% faster | Design fidelity and accessibility |
| Checkout, cart and other complex flows | ~30% faster | Business-logic validation |
| Verifying the live system behaves identically | ~0% | All of it |
Why the total does not drop by 70 percent: those percentages apply to writing code. Every migrated page still needs an engineer to review the output, compare it against the live system, test real user flows, deploy, flip and watch it. The published cases where AI rewrote a system in days all had one thing in common, an existing test suite complete enough to judge every change automatically. Where that automatic verdict exists, AI genuinely runs at twice the pace. Where the verdict is a human looking at a live system, verification sets the clock. That is why the foundation stage builds a parity test suite for the money-critical logic first.
Every phase starts with sandbox testing and validation in parallel environments.
Then: changes go out incrementally once the system is stable.Business-critical workflows and dependency chains are mapped with static and dynamic analysis before anything migrates.
Then: the migration order follows the map, not the org chart.Clear rollback points, database diff checks, contract testing, feature flags and blue-green delivery.
Then: a bad flip is reversed in minutes, not in a release cycle.Pricing, discount and order calculations must produce identical results in both implementations. Any divergence would show up as billing discrepancies.
Then: both run in parallel during QA until the results match.Age alone does not decide the approach. Framework support status, test coverage, the hiring market for the stack and release frequency do, and the assessment scores these before any code is touched.
Server-side rendering and static generation are chosen per route rather than for the whole application: public pages are pre-built and served as full HTML, which is what search engines and AI crawlers need, while personal pages such as cart and account stay dynamic because crawlers do not index them. Third-party prerendering services can be retired page by page as routes move over.
Thousands of live exam sessions ran daily while dozens of interconnected applications moved to the cloud.
Three disconnected systems with limited documentation and workflows too critical to interrupt.
Nothing moves without simulation, rollback protocols and real-time observability. Every phase starts with sandbox testing in parallel environments, and a migrated route goes live only after it is proven, with the manifest entry ready to be reversed.
No. The legacy app keeps running unchanged behind the front door and keeps serving every route that has not migrated. It is retired only when the manifest no longer points to it, at which point the proxy and the temporary bridges are deleted.
The route goes back to the legacy app with one line in the manifest and a deploy of roughly two minutes, or with no deploy at all if flips are driven by an environment variable. That decision is made during the foundation stage, with knowledge of your pipeline.
Framework-free business logic is extracted into a shared package that both applications use, and a parity test suite proves both produce identical results. Both implementations run in parallel during QA to catch any divergence before it reaches an invoice.
No, it fits the same shape. Migrating legacy applications to the cloud happens per route as well: a migrated route can already run on the new infrastructure while the rest of the system stays where it is, and the manifest decides which one answers. Lift-and-shift, re-platforming and re-architecting are chosen per component, not for the whole estate at once.
Yes. Each package ships complete and reversible, so you can stop at any package boundary with the system fully working, and resume later without unwinding anything.
No. The choice is made per application: refactor when the code still holds business value, rebuild when the framework is dead, replace when the function is a commodity, retain when nothing is gained by touching it. Staged modernization ships value from the first package.
Companies typically notice tangible financial and operational benefits within 3 to 6 months of beginning modernization, such as lower infrastructure costs, better application performance and reduced maintenance costs.
We choose tools that build on your team's current skills, and provide hands-on training, clear documentation and knowledge transfer as part of delivery.
30 minutes on your stack and constraints: which path fits, what the first two-week package would deliver, and what has to be true before anything is switched over.