Any industry · Software delivery

Legacy modernisation and code migration

Migrate old PHP, Java or .NET applications service by service with Claude Code: characterisation tests first, then codemods and a pull request per service behind CI gates.

  • ClaudeAnthropic
  • Typical timeline: Pilot in 2–4 weeks

The problem

Old PHP, Java or .NET applications and unmaintained frameworks block new features, and a full rewrite is risky and slow.

  • Every new feature fights the old codebase.
  • Nobody wants to own the big rewrite.
  • Big-bang migrations stall halfway.

How we solve it

Claude Code maps the system, writes characterisation tests and codemods, and opens a pull request per service, with parallel sub-agents, CI gates and staged rollout, so the system moves forward one safe step at a time.

It plugs into GitHub or GitLab, Your CI, Jira or Linear and AWS, Google Cloud or Azure, so nothing you rely on today is replaced. The architecture below shows each step and which model does the work.

Architecture

From your stack, through the AI layer, to numbers you can track

Each step names the model or system doing the work. Writes to your systems wait for a person to approve them.
Legacy modernisation and code migration. Your systems (GitHub or GitLab, Your CI, Jira or Linear and AWS, Google Cloud or Azure) connect to Softpiper's AI layer, which runs these steps: Map the system (Claude Code); Characterisation tests (Claude Code); Plan per service (Claude Opus); Migrate (Sub-agents · Routines); Gate (Your CI); Roll out (AWS · Google Cloud · Azure). Outcomes are measured as services migrated per sprint, test coverage, regression incidents and build and deploy times.

Your stack

  • GitHub or GitLab
  • Your CI
  • Jira or Linear
  • AWS, Google Cloud or Azure

AI layer

Softpiper AI layer

  • Claude
  1. Map the system, using Claude Code

    Modules, dependencies, risky areas and test gaps are mapped.

  2. Characterisation tests, using Claude Code

    Current behaviour is captured in tests before anything changes.

  3. Plan per service, using Claude Opus

    A migration plan sequences services by risk and value.

  4. Migrate, using Sub-agents · Routines

    Codemods and a pull request per service, with sub-agents working in parallel.

  5. Gate, using Your CI

    CI runs the full suite on every pull request; engineers review before merge.

  6. Roll out, using AWS · Google Cloud · Azure

    Feature flags and a staged rollout to your target cloud.

Outcomes you measure

  • Services migrated per sprint
  • Test coverage
  • Regression incidents
  • Build and deploy times

Why this model

Why Claude

We choose per task on capability, cost and where your data must stay. Final versions are picked at kickoff.
ClaudeAnthropic

Anthropic positions Claude Opus for long-running agentic coding: it plans migrations, writes codemods and works through parallel sub-agents, while Routines or Managed Agents run overnight batches.

Standardised on Google? For Google Cloud targets, Google's application-modernisation tooling can complement the migration.

Delivery

What you get, how long it takes, and how we keep it safe

Guardrails

  • Characterisation tests before any change.
  • Feature flags and staged rollout.
  • Engineers review and approve every merge.
  • A rollback plan for every service.

Plus the guardrails on every build: facts from your systems, approvals for writes and money, a human one step away, audit logs and evals. See all

Deliverables

  • Codebase map and migration plan
  • Characterisation test suite
  • Migrated pilot service
  • Migration playbook for the remaining services
  • CI and rollout configuration

Typical timeline

  1. Discovery and pilot service2–4 weeks
  2. Phased rolloutPlanned per service

A planning range for a first production release. We confirm scope, price and dates in a tailored proposal.

KPIs to track

  • Services migrated per sprint
  • Test coverage
  • Regression incidents
  • Build and deploy times
  • Engineering hours per migrated service

Goals we agree with you and measure from a baseline. They are what we track, not results we promise.

Related services

Our work in this space

What we've built for growing businesses

Sites and products we've shipped for businesses in this sector. They show how we work; they are not deployments of this playbook.
  • Greenberg Engineering home page: “Create the future with us” beside the Greenberg monogram on black
    Live

    Corporate platform on Next.js · Engineering and infrastructure

    • Next.js
    • Corporate platform
    • Engineering

Pip · Softpiper's AI

Ask Pip about this playbook

Ask Pip how this would work for you

Pip is Softpiper's AI. Tell it what you run today and it will walk through how this playbook fits, what we would build first and a tailored price range. Or book a call with the team.

Book a call