AI-assisted delivery for mid-market software

Legacy System Modernisation

Modernise the parts of your stack that are slowing the business down — without a full rewrite, a frozen roadmap, or a high-risk migration. Lanex pairs AI-assisted engineering with senior delivery experience to cut cycle time, clear backlog, and reduce integration risk in 4 to 8 week sprints.

Lanex senior architects reviewing a system modernisation plan with integration diagrams on a glass wall
Best Fit

Who this is built for

AI has not removed the need for engineers in mid-market software — it has raised the bar for how much output a team must deliver. Lanex is strongest when the system is complex enough that off-the-shelf AI alone cannot replace it.

Mid-market businesses running revenue-critical software on aging stacks

Teams blocked by integration debt, broken deploys, or knowledge sitting with one or two people

Companies under compliance, audit, or vendor pressure that cannot risk a rebuild

What we don't do

We avoid full-platform rewrites, multi-quarter strategy decks, and capacity-only contracts. The work is scoped, time-boxed, and tied to a measurable production outcome.

Typical engagement4 to 8 week sprint, 2–4 person AI-assisted pod, weekly outcome reporting.
Common stacksLegacy .NET, classic PHP, Java monoliths, on-prem databases, custom ERP integrations.
Two Failure Modes

Why most legacy modernisation projects stall

The buyers we speak to are usually stuck between two bad options. Lanex was built for the third path.

The full-rewrite trap

Most modernisation projects fail because the team tries to rebuild everything at once. We don't. We modernise the system one production-critical slice at a time, in 4 to 8 week sprints with measurable outcomes per sprint.

The keep-the-lights-on trap

The other failure mode is patching forever. AI-assisted refactoring lets a small team move legacy code through structured upgrades faster than a traditional offshore squad, without disrupting daily operations.

Outcomes, Not Capacity

What we measure and report on

Every sprint produces a Friday outcome report. We do not bill on engineer-hours alone. We bill against agreed outcomes, with the metrics visible to your team.

Reduce cycle time

Cut the time from feature request to production by replacing manual handoffs with AI-assisted code review, testing, and documentation generation.

Clear the backlog

AI-assisted engineers move through legacy refactors, integrations, and tech-debt tickets at materially higher throughput than headcount-only teams.

Lower integration risk

We modernise alongside your existing system, not over the top of it. Each release is observable, reversible, and tested against the real production data shape.

Pass audit and compliance

Documentation, traceability, and access control are part of the delivery, not a follow-up project. Regulated industries get audit-ready artefacts as a side-effect of the work.

How Engagement Works

From brief to first production release

1

Discovery sprint (1 week)

We map the system, the risk surfaces, and the highest-leverage modernisation slices. You get a written brief — what we'd ship in the next 4 to 8 weeks and what the measurable outcome is.

2

Pilot delivery (4 to 8 weeks)

A small AI-assisted Lanex pod (typically 2 to 4 people) ships the first slice into production. Outcome metrics — cycle time, backlog, defect rate — are reported every Friday.

3

Expand or stop

If the pilot hits the agreed outcome, we plan the next slice. If it doesn't, you stop. There is no long lock-in contract and no penalty for ending the engagement after a pilot.

No lock-in. No multi-quarter discovery.

Scope one sprint, ship one production outcome, decide whether to keep going. That is the entire engagement model.

Scope a Pilot

Ready to modernise the system that's holding the business back?

Tell us the slice of the system that is slowing delivery, and we'll come back with a 4 to 8 week pilot scope, the outcome metric, and the team needed to ship it.