Ryz legacy application modernization teams move aging systems onto modern platforms one piece at a time: they wrap old behavior in tests, re-platform to current runtimes and the cloud, refactor monoliths, and replace components behind a strangler-fig facade while the business keeps running. Our engineers come from the top 1% of the people we interview, work on US business hours, and have done this on Java EE, .NET Framework, classic ASP, PHP and COBOL-adjacent estates. This page covers engineering-led modernization; if you want AI pods to speed up code migration with LLM assistance and human review, see AI legacy modernization.
Talk. We learn why modernization is on the table now: end-of-support runtimes, security findings, hiring difficulty for the old stack, release speed or hosting cost. Then we look at code, deployment and the people who know the system.
Match. We propose engineers who can read the old stack and build in the new one, for example people who know both Java EE and Spring Boot, or Web Forms and ASP.NET Core.
Join. The team works in your repos, CI and environments, pairs with the engineers who hold the system knowledge, and joins your standups and release process.
Grow. Add engineers as more components move, bring in cloud or data engineers for later phases, or hand the modernized system to your team.
In week 1, the team typically gets the system building and running locally, reads the code paths with the most change and incidents, and interviews the people who support it. By month 1, characterization tests cover the first slice, CI runs on every change, and the first component is selected with a cutover and rollback plan. By month 3, the usual picture is the first slice running in production on the new platform, the routing layer in place, and a sequenced plan for the rest based on what the first slice taught.
The classic failure is the big-bang rewrite: a team spends a long time rebuilding the system from documents, the old one keeps changing underneath them, and the cutover reveals behavior nobody wrote down. Senior engineers avoid that path and guard against the quieter failures too:
Engineering-led modernization is the right approach when the hard part is design, sequencing and data. When the bulk of the work is high-volume code translation, the AI-assisted variant adds LLM-based conversion with human review on top of the same practices.
Typical Ryz cost is $7,000 to $15,000 per engineer per month. Mid-level engineers are $7,000 to $10,000, senior engineers are $10,000 to $15,000, and leads are $15,000 or more, quoted per team.
Project cost is team size × duration × monthly rate. Every quote is scoped per team, and you get a plan, a price and the names of the people before you start.
A dedicated development team fits most modernization programs, because sequencing, testing and cutovers need one team that owns the outcome. If your engineers lead the program and need senior capacity, staff augmentation adds engineers who join your sprints and report to your leads. See our hire Java developers and hire .NET developers pages for profiles. When the move also changes hosting, our cloud migration teams run that part.
If you want to replace the system with a commercial package and only need configuration, the vendor or its implementation partner fits better. If modernization is part of a board-level transformation program with organizational change management, a large consultancy should lead. If your team works on European or Asian hours, a global network will give you better overlap.
Rarely a full rewrite. Incremental replacement with the strangler-fig pattern keeps the system running, delivers value early and exposes hidden behavior one slice at a time. A rewrite can make sense for small, well-understood systems with good test coverage.
Cost is team size × duration × monthly rate. Typical Ryz rates are $7,000 to $15,000 per engineer per month, and a lead plus two senior engineers starts at $35,000 per month. Duration depends on system size and how many slices you modernize.
After the scoping call we propose a team with names. Most of the timeline depends on scope and on your onboarding, especially access to source code, environments and the people who know the system.
This service is engineering-led: architecture, tests, re-platforming and refactoring by senior engineers. AI legacy modernization uses AI pod teams to add LLM-assisted code translation, with human review, which helps most when there is a large volume of similar code to convert.
Yes, that is the usual starting point. Teams build characterization tests and documentation as they go, working with the people who support the system today.
Questions we didn't answer? Email info@ryzlabs.com.
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