Our system cannot take downtime. Is migration still possible?

Yes, using dual-write, replication, and traffic-shifting patterns that keep both platforms live during transition. Cutover becomes a routing change you can reverse in seconds.

How do you prove nothing broke?

Automated regression suites captured against the current system before migration, plus data reconciliation and a monitored soak period at each wave.

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

Platform Migrations & Version Uplift

Get current, and stay current, without a weekend of downtime.

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Near-zero

Planned downtime at cutover

Tested

Rollback path before every wave

Supported

Versions across the estate

Overview

What Platform Migrations & Version Uplift means at NeonAITech

Unsupported runtimes, databases, and frameworks are a security and hiring liability. We plan and execute migrations and version uplifts — cloud moves, database upgrades, framework jumps — with dependency analysis, automated regression testing, and rehearsed, reversible cutovers.

Tools & Platforms

AWS DMS
Terraform
OpenRewrite
Playwright
Renovate
Kubernetes

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

What We Deliver

Migration Assessment & Plan

Dependency analysis, risk scoring, effort estimation, and a wave plan sequenced so the riskiest unknowns surface early.

Execution & Cutover

Rehearsed migrations with parallel running, data validation, and a documented rollback that has actually been tested.

Continuous Currency

Automated dependency updates and an upgrade cadence that stops you sliding back into unsupported versions.

Capabilities

Inside the Engagement

Data-centre to cloud and cloud-to-cloud moves

Database engine and major-version upgrades

Framework and runtime uplift with codemods

Automated regression and smoke suites

Zero and near-zero downtime cutover patterns

How We Work

A delivery rhythm you can see into

Every Platform Migrations & Version Uplift 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.