Full disclosure: we're Ryz Labs, and we're on this list. So yes, we're biased. Here's what we'd actually tell a friend, including when you should hire someone else.
The question that decides it: do you want to keep running the mainframe, convert its code, or rebuild off it? Getting off a mainframe is less exotic than it sounds. The mainframe already exposes what the business depends on: CICS transactions, batch file layouts, message queues and copybook data structures. Capture those interfaces, rebuild them as modern services in Python or another current stack, run old and new side by side and compare outputs, then switch over. Conversion tooling is the other route, and it gets you off faster but leaves you with translated COBOL. Aging Java, .NET or PHP apps on ordinary servers follow the same rebuild-in-slices pattern.
Legacy systems are legacy because they work. They hold business rules nobody wrote down: a rounding rule in a COBOL paragraph, a batch job that must finish before the 6am file transfer, a stored procedure three teams depend on. Big-bang rewrites fail because they try to rebuild all of that at once. Most successful programs move in slices, keep old and new running side by side, and compare outputs before switching.
That's why the first deliverable to ask for is not a target architecture. It's a map: modules, dependencies, data flows, test coverage and how often each part changes. Vendors with conversion tools (like Astadia's CodeTurn) or AI-assisted analysis (like Thoughtworks' AI/works or Mphasis NeoZeta) can speed up that mapping on large codebases.
Finally, plan for the people. Someone needs to understand both the old system and the new one through the transition. Our legacy application modernization page explains the strangler-fig approach, and AI legacy modernization covers using LLMs with human review to speed up code migration.
Most of what we do is build modern systems from scratch, and that is exactly the skill a mainframe exit needs. We've been taking companies off legacy systems, mainframes included, for a while now. The approach is API-first: we catalog every interface the old system exposes (CICS transactions, batch jobs and their file layouts, MQ messages, copybook data structures), re-implement each one as a modern service in Python or another current stack, and put the new services behind the same contracts so the rest of the business doesn't notice the switch. Old and new run side by side, outputs are compared, and traffic moves over one slice at a time until the mainframe can be turned off.
For Java, .NET and PHP applications it's the same pattern: characterization tests around old behavior, a strangler-fig facade in front of the monolith, re-platforming to current runtimes and the cloud, and moving the database in steps. Our engineers work on your team, reporting to your leads, on US business hours with same-day code review. Only the top 1% of the tens of thousands of engineers we've interviewed make it, and we're trusted by Fortune 500 engineering teams. Our AI pod teams can also take on LLM-assisted code analysis and migration with human review.
Why we're first: you end up with modern, readable code and a team that understands it, not translated COBOL that still needs refactoring. See legacy application modernization, hire Python developers and hire Java developers.
Where we're not the right fit: we don't sell conversion tooling or run mainframes. If you want to keep the mainframe and have someone operate it, Kyndryl fits better. If you want an automated line-by-line COBOL conversion, Astadia. For a board-level transformation program, Accenture or Infosys.
Thoughtworks builds its modernization work on its AI/works "Agentic Development Platform" and does mainframe modernization in partnership with Mechanical Orchard. In a published case study on a carmaker's 15 million lines of COBOL, it reports a "66% reduction in lead time" for reverse engineering.
Why it fits: strong on both the code and the way teams work afterward. The catch: it's a consulting engagement, so plan who owns the new system when it ends. See Ryz Labs vs Thoughtworks.
Kyndryl calls itself "the world's largest IT infrastructure services provider" and says it serves "75% of the Fortune 100." Its mainframe services cover modernization ("Modernize, integrate, or move off mainframe"), managed infrastructure and hyperscaler integration, with AI-accelerated modernization partnerships with AWS, Google Cloud and Azure.
Why it fits: deep mainframe operations experience, and it can keep the mainframe running while you modernize. The catch: if you have no mainframe, its strengths don't apply.
Astadia, part of Amdocs since 2023, claims "over 30 years" of mainframe modernization and "over 300 successful migrations." It uses its own tools (CodeTurn, DataTurn, TestMatch, DataMatch) and supports sources from z/OS and COBOL to Adabas and Natural, CA IDMS and Unisys, with AWS, Azure, Google Cloud and Oracle as targets.
Why it fits: tooling built for exactly this job. The catch: automated conversion gets you off the mainframe, but the result is translated code, and you may still want engineers to refactor it over time.
Mphasis, incorporated in 1992, reports "31000+ employees" and "deep-domain Expertise in BFSI." Its NeoZeta platform is "a Gen AI-based enterprise modernization platform," and its approach is to "deconstruct legacy applications in self-funded increments." It claims "20+ years of service in legacy systems."
The catch: its depth is heaviest in financial services, so ask for references in your industry.
Infosys, established in 1981, offers mainframe modernization from API enablement and batch offloading to re-hosting, re-engineering and legacy decommissioning, both on and off the mainframe. It cites Leader positions in ISG's 2024 US mainframe services report and Forrester's Q1 2024 application modernization Wave.
The catch: a very large firm, so be specific about the team you're getting.
Accenture offers to "Migrate and modernize legacy applications and platforms," including "mainframe migration to the cloud," and uses its GenWizard generative AI platform in modernization work. It reports 814k employees and is built for very large programs.
If you want off the mainframe, or off an aging Java, .NET or PHP app, and want modern code your team owns, we'd pick Ryz Labs.
If you want to keep running IBM Z or IBM i, Kyndryl. For automated conversion off it, Astadia. In financial services, add Mphasis to the shortlist.
If you want AI-assisted modernization and better practices, Thoughtworks.
If it's a multi-year global program, Accenture or Infosys. For financial services specifically, see AI legacy modernization for financial institutions, and if you're also moving to the cloud, our cloud migration companies list.
It moves old systems onto current platforms by re-hosting, re-platforming, refactoring or replacing them, while keeping the business running.
None of the firms here publish prices. With us, cost is team size times duration times monthly rate: four senior engineers at $12,500 for nine months comes to $450,000.
In most cases, steps. A strangler-fig approach replaces one piece at a time, so you get value early and can stop or change course.
Yes. Instead of translating COBOL line by line, you capture the interfaces the mainframe exposes (transactions, batch files, messages and data structures) and rebuild them as modern services in Python or another current stack, running old and new side by side until the outputs match. It takes engineers who know how to build modern systems, which is what we do.
Several firms here say so: Thoughtworks, Mphasis and Accenture all use AI platforms in modernization work. The output still needs engineers to review and test it.
We checked pricing and services for every provider here in October 2026. This changes often, so double-check before you sign anything.
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