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Automation and Integrations

Replace an aging system step by step, without stopping the business

Big-bang rewrites of business-critical systems often fail. We modernize in small, safe steps: new parts take over one by one while the old system keeps running.

The problem

The problem this solves

Many businesses depend on a system built ten or twenty years ago. It works, and it encodes years of business rules and exceptions. But it is written in a technology few developers know, hosted on aging servers, hard to connect to anything new and risky to change. Every year the technical debt grows and the people who understand it get harder to find.

The obvious answer, a complete rewrite, is the riskiest. Rewrites take longer than planned, miss business rules nobody remembered, and ask the business to switch everything on one day. Many are abandoned halfway, leaving two systems to maintain.

We use a gradual approach, often called the strangler pattern. First we capture how the current system behaves with characterization tests, sometimes called golden-master tests, so we can prove the new parts do the same thing. Then we build new components around the old system, route one feature at a time to the new code, and keep data in sync, often one way at first, until the old part can be switched off.

AI has made this much more practical. It can read and summarize large, old codebases quickly, explain undocumented business rules, generate characterization tests and draft migration plans. People still decide what to keep, what to change and when each switch happens.

This is exactly the approach described in our beach rental booking system case study, where a long-running booking system had to keep taking bookings while a modern stack was planned alongside it.

What you get

What you get

  • System analysis

    Code, data, integrations and business rules documented, many for the first time.

  • Characterization tests

    Tests that capture current behavior so changes can be proven safe.

  • Modernization roadmap

    The order in which parts are replaced, with risks and milestones.

  • Routing layer

    A layer that sends each feature to old or new code, switchable per feature.

  • Data sync

    Sync between old and new databases while both are in use.

  • New components

    Modern replacements for each part, built with tests and documentation.

  • New integrations

    APIs so the business can finally connect the system to modern tools.

  • Decommissioning

    A safe shutdown of old parts once the new ones have proven themselves.

How we build it

How we build it

  1. 1

    Understand

    AI-assisted reading of the codebase, plus interviews with the people who use it.

  2. 2

    Protect

    Characterization tests written around the most important behavior.

  3. 3

    Plan

    A roadmap that starts with the part that gives the most value or risk reduction.

  4. 4

    Replace piece by piece

    Each part rebuilt, tested against the old one and switched over.

  5. 5

    Retire

    Old parts switched off once nothing depends on them.

AI and people

Where AI helps, where people decide

AI makes the repetitive parts faster. The decisions that shape your product stay with experienced people.

Where AI speeds things up

  • Reading and summarizing large legacy codebases.

  • Explaining undocumented business rules.

  • Generating characterization tests from real behavior.

  • Drafting migration scripts and data sync code.

  • Producing documentation of the old and new systems.

Where people decide

  • Which parts to replace first, and which to keep.

  • Which old rules are still correct, and which are bugs.

  • The target architecture and technology.

  • When each switch is safe.

  • When the old system can finally be turned off.

Is this right for you?

When this is the right choice

A good fit when

  • A critical system is hard to change, host or hire for.

  • You cannot afford for the business to stop during a replacement.

  • Business rules live in code nobody fully understands.

Consider something else when

  • The system is small and a clean rebuild is low risk.

  • An off-the-shelf product can replace it with little customization.

Timeline and cost

What affects the timeline and cost

We do not publish fixed prices because scope drives cost. How we estimate.

  • System size

    More features and code mean more to analyze and replace.

  • Documentation

    Undocumented systems need more investigation.

  • Data complexity

    Complex or inconsistent data makes sync and migration harder.

  • Integrations

    Systems that depend on the old one must be moved carefully.

  • Uptime needs

    No downtime allowed means more parallel running.

  • Business involvement

    Rules must be confirmed with the people who know them.

Keep exploring

FAQ

Questions about legacy modernization

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