Application modernization without stopping the business.

Application modernization is rebuilding the software a business already runs on so it is safe to change again, while the business keeps using it. It covers the code, the data and the platform underneath: a mainframe program rebuilt as services, a monolith split where it pays, a framework brought back into support. Done well, it moves one module at a time, each proven against the old system before its traffic moves.

They are the routes a module can take: retire, retain, rehost, replatform, refactor, rearchitect and rebuild, with replace, buying a product, as the eighth that most frameworks add. Retire and retain change only the plan; rehost and replatform change where it runs; refactor, rearchitect and rebuild change the code itself. An estate almost always ends up with a mix, so the route is chosen per module from its value to the business and the condition of its code.

When changing it has become the risk. The signs are releases done by hand or a few times a year, frameworks past their support dates, rules only one long-serving engineer understands, data the rest of the business cannot reach in time, and AI projects that stall because the system has no API. Two or more together, and the system is deciding what the business can do.

In steps, in almost every case. A full rewrite freezes the business while the new system chases a moving target, then goes live all at once. Moving one module at a time behind the interfaces the system already has delivers value from the first module, keeps every step reversible, and still ends with the old system switched off. A module that cannot be saved is rebuilt inside that same stepwise plan.

Cloud migration changes where software runs; modernization changes the software itself. Rehosting a system on cloud servers keeps the same code, the same release pace and the same risks. Modernization restructures or rebuilds the code and the data so the system can change quickly, scale, and be used by other systems and by AI agents. Many programs do both, module by module.

Old and new run side by side, and live traffic moves between them at a routing gateway in steps. A route starts on the new service at a small share, rises as the numbers hold, and can be sent back to the old path in one step at any point. Change data capture keeps the data in step, so either side can serve a request while the move is under way.

By making both answer the same requests and comparing every field. Characterization tests pin what the old system does today, past batch runs are replayed through the new code, and live requests go to both in a parallel run. Every difference is traced to its cause and closed, and a module takes traffic only once your people sign its parity report. Period-end runs must reconcile before the old module is switched off.

In batches that are reconciled before anything depends on them. Change data capture keeps the old and new stores in step, and after every batch the row counts, the control totals and the checksums are compared. Reads move first and writes after, and the old store stays until you sign the reconciliation.

Its traffic goes back to the old path in one step. The old module stays running and in step until the new one has passed the period-end runs, so rolling back loses nothing. The cause is found, a test that would have caught it joins the suite, and the route moves again only after its parity report is signed again.

AI translates COBOL quickly; accuracy comes from what surrounds the translation. Much of a COBOL program's behavior lives outside the source, in packed-decimal arithmetic, compiler options, EBCDIC data and the batch schedule, and a line-by-line translation also carries the old structure into the new language. We use models to read, map and draft, rebuild each module as clean services, and prove the result against the old system's own outputs before it takes traffic.

For the work that used to take longest: reading. Models read every program, copybook, job and table, map who calls what, explain each module in plain words, draft the business rules and the tests that pin them, and make the mechanical edits of framework upgrades. Engineers decide the architecture, check each rule against production records, review every change and own every release.

No. Models run inside your environment, or are called through enterprise endpoints configured for zero data retention, and nothing is used for training. Which repositories and data a model may read is agreed in writing before discovery starts, and every model call is logged.

It depends on the size and condition of the code, the data to move and how clean it is, the number of systems it talks to, the downtime the business can accept, and the evidence your regulators expect. That is why the work runs in phases: discovery first, then each phase scoped in writing and approved before it starts, so the cost of every step is known before you commit to it.

Discovery ends in a dated plan for your estate. The length of the whole program depends on the number of modules and the period-end runs each must pass, and the first module goes live long before the last one moves, so the business sees results from the first phase.

No. Some workloads are best left on the mainframe, and the plan says which. Discovery weighs each one: modules that change often or hold the business back move first, stable high-volume batch may stay and be opened up through APIs, and the end state can be hybrid by design. The decision is made per workload, in writing.

Yes. The first ask is access: the source, the servers and DNS, the hosting and license accounts, and an hour with whoever used to call the vendor. From that we rebuild the map nobody wrote down, what runs where and what stops if a piece is turned off. Accounts and credentials move into your own names as we go, so nothing later depends on the previous team being reachable.

No. The code is in your repositories from the first commit, in standard languages on open platforms, with no runtime of ours in the path and nothing to license from us. Runbooks, rules and parity reports are delivered as the work goes, and your engineers pair with ours, so your team or any other can carry on without us.