Our legacy system has no documentation or original developers. Can you still help?

That is the common case. AI-assisted analysis reconstructs data flows and business rules from the source itself, and we validate every finding with characterisation tests against the running system before changing anything.

Can the business keep requesting new features during modernisation?

Yes, and it should. Incremental migration means the system stays releasable throughout; we sequence work so feature delivery and modernisation share the same pipeline.

How quickly can an engagement start?

Discovery usually begins within one to two weeks of scope agreement, and a delivery team is typically mobilised within three to four weeks depending on the skills involved.

Can you work alongside our in-house team?

Yes — most of our engagements are blended. We work in your repositories, ceremonies, and tooling, and we plan for knowledge transfer from the start so capability stays with you.

How are engagements priced?

Fixed price for well-bounded projects, monthly capacity for dedicated pods, and outcome-linked SLAs for managed services. We are explicit about assumptions and what would change the number.

NeonAITech services — AI and data engineering, product engineering, cloud and DevOps, managed operations, security and quality

Intelligent Application Modernisation

Retire technical debt with AI doing the archaeology.

Book Free Consultation All Services

40–60%

Faster than a manual rewrite

Zero

Big-bang cutover risk

50%

Lower ongoing maintenance cost

Overview

What Intelligent Application Modernisation means at NeonAITech

Legacy systems are expensive to change and risky to replace, usually because nobody fully understands them any more. We use AI-assisted code analysis to reconstruct the behaviour hidden in old codebases, then modernise incrementally with the strangler-fig pattern — no big-bang rewrite, no frozen roadmap.

Tools & Platforms

Claude
ArchUnit
Testcontainers
Kubernetes
Strangler-fig
OpenRewrite

We are not tied to a single vendor — the stack follows the problem, your existing estate, and your team’s skills.

What We Deliver

Codebase Comprehension & Assessment

AI-driven analysis that maps dependencies, dead code, business rules, and risk, producing a costed modernisation roadmap.

Incremental Re-Architecture

Strangler-fig migration that peels capabilities off the monolith behind a routing layer, with rollback available at every step.

Language & Framework Uplift

Assisted translation from legacy stacks with characterisation tests that prove behaviour is preserved, not merely reimplemented.

Capabilities

Inside the Engagement

Business-rule extraction from legacy code

Characterisation and golden-master testing

Monolith-to-service decomposition

Database and integration migration

Parallel run and phased cutover

How We Work

A delivery rhythm you can see into

Every Intelligent Application Modernisation engagement runs the same four phases, with AI used wherever it removes effort rather than adds novelty.

01
Discover
We map the current state, agree the outcome, and size the work — so scope is a shared decision, not a surprise.
02
Design
Architecture, delivery plan, and success measures are set before build, with costed options where trade-offs exist.
03
Build
Short increments with working output you can review, steer, and stop — never a black box until go-live.
04
Operate
We measure against the agreed outcomes, hand over documentation, and stay on for support where you want it.

Engagement Models

Buy it the way that fits

Fixed-Scope Project

A defined outcome, timeline, and price. Best when requirements are clear and the deliverable is well bounded.

Dedicated Pod

A cross-functional team working to your backlog and priorities, scaling up or down with a month’s notice.

Managed Service

Ongoing ownership against agreed SLAs, with a share of capacity reserved for continuous improvement.