Govern & Modernize

AI-assisted refactoring for legacy code.

A named senior engineer uses Copilot, Cursor, or Claude Code to read old code, lock what it does with tests, and land small changes a person still approves. The system stays up.

What you get

The module stays. The language stays. What changes is how safe it is to touch. We start with characterization tests that pin what the code does today, including the odd cases nobody wrote down. Then Copilot, Cursor, or Claude Code may propose a small change. A named person reads the diff and owns the merge. We measure the outcome: a test that fails when behavior drifts, a function a new engineer can read, and a path you can change next month without a weekend outage. Moving the system onto a stack your team can keep is legacy software modernization. Putting a stable API in front of the system you already run, so new work can ship while the old system stays up, is API-first modernization for older systems. This engagement is the code you already have. Same idea, other angles. A phone or tablet app you would rather refresh than abandon is Rebuild or refresh an existing app. People who do this work inside your team are Staff augmentation for legacy modernization. A patient portal that needs the same care is Patient portal modernization. We have been shipping software since 2002.

  • Characterization tests before the first refactor
  • Small pull requests a person can read in one sitting
  • A named reviewer on every merge
  • Copilot, Cursor, or Claude Code may propose the change. A human approves it
  • Outcomes you can measure: pinned behavior, a module someone new can read, no weekend outage
  • The stack stays. Client code stays in your environment

What we hand back

Tests that pin today's behavior

Small diffs a person approved

A module the next change can touch

A number for what got safer

Why teams call Maxiom

The first change to old code should be a test.

The assistant rewrites a file nobody understands

A long diff can look finished and still change a rule the business depends on. If you cannot say what the code did yesterday, you are not ready to change it.

The new tests only repeat the new code

Tests written after the refactor often prove the new version agrees with itself. They do not prove you kept the behavior customers already rely on.

The branch sits for three weeks

A rewrite in one pull request is too big to review. It stalls, then it lands on a Friday because someone is tired of the conflict.

How an engagement works

Kickoff

  1. 01

    Align

    First call · 30 minutes

    We look at the module you are afraid to touch, what must keep working, and whether the real job is a refactor or a move to a new stack.

    • The behavior that cannot change
    • The path a new engineer cannot read
    • Whether modernization or an API in front is the better first step

    You get: a clear yes or no on fit

  2. 02

    Scope

    NDA · written plan

    You get a written slice: the tests that pin today's behavior, the changes we will attempt, and the person who approves each merge.

    • Deliverables, timeline, and a named engineer
    • NDA signed before access
    • Read-only until the scope says otherwise

    You get: a committed written scope

  3. 03

    Execute

    Tests, then small changes

    The named engineer writes characterization tests first, then lands small reviewed changes. The assistant may draft. A human owns every merge.

    • Tests that fail when today's behavior drifts
    • Pull requests sized for one review
    • Client code stays in your environment

    You get: progress you can inspect

  4. 04

    Handoff

    Tests · debrief

    You keep the tests, the smaller module, and a walkthrough of what changed and what we refused to change.

    • The characterization suite in your repo
    • A note of the behavior we pinned
    • What to watch the first week after the change

    You get: old code you can change again

Scoping

Talk to an engineer about AI-assisted refactoring for legacy code.

Tell us your stack, timeline, and constraints. We will tell you honestly whether Maxiom is the right fit, and what a scoped engagement would look like.

  • Free 30-minute scoping call: no hard sell
  • Written scope before any repository access
  • Senior engineers only on the work that matters
  • Response within one business day

Prefer calendar? Book a scoping call · hello@maxiomtech.com

Request a scoping conversation

Share a few details and we will follow up within one business day.

Frequently asked questions

The first conversation is scoping. Stack, constraints, and whether we are the right fit.

What is AI-assisted refactoring for legacy code?

A named engineer uses Copilot, Cursor, or Claude Code to read old code, pin what it does with tests, and land small changes a person still approves. The language and the system stay. The code gets safer to change.

Why do you write characterization tests first?

Old code often holds rules nobody documented. A characterization test records what the code does today, including the odd cases. You change the code only after a failing test would tell you the behavior moved.

Who approves the merge?

A named person on your side or ours. The assistant can propose a diff. It does not approve its own pull request. If the diff is too big to read in one sitting, it is too big to merge.

How is this different from legacy modernization?

Legacy modernization moves an aging system onto a stack your team can keep, in phases, while production stays up. Start there when the runtime itself has to change: legacy software modernization. This engagement leaves the stack in place and makes the code you have safer to change.

How is this different from an API in front of the old system?

An API in front lets new work call the system you already run without rewriting it. That is API-first modernization for older systems. This page is the code inside the system: tests, small diffs, and a human on every merge.

Which tools do you use?

Copilot, Cursor, and Claude Code, inside your repository and your rules. They draft. They do not choose the behavior to keep, and they do not merge. Client code stays in your environment.

What do we measure?

Behavior that stays pinned, a module a new engineer can read, and a change that ships without a weekend outage. We write those down before the work, and we check them at the end. A big drop in line count with no tests is not a result.

What if the old system is a mobile app, a patient portal, or paper inspections?

Say so on the first call. A phone or tablet app you would refresh is Rebuild or refresh an existing app. A patient portal is Patient portal modernization. People who join your team to do this work are Staff augmentation for legacy modernization.

How do we start?

A 30-minute scoping call. Bring the module you are afraid to touch and the name of the person who can say what must not change. We will tell you if the right next step is this refactor, a move to a new stack, or someone else. You can contact us or use the form on this page.

Not sure this is the right engagement? That is what the first conversation is for.

Tell us your stack, regulatory context, and timeline. We will tell you honestly whether Maxiom is the right fit.

  • NDA signed before access
  • Senior engineers every time
  • Written scope before work
  • Client code stays with you