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Modernize legacy stacks safely, with AI doing the volume.

Senior judgement on the architecture, agents on the conversion work. Move off the framework, the database, or the cloud without 18 months of disruption.

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Service
Engineering
3-5×
Faster than hand-migration
Zero
Production downtime, by design
100%
Test coverage carried forward
Plain English
Migration documented end-to-end
Overview

Why this engagement exists.

Migrations fail two ways: they take twice as long as the estimate, or they break production halfway through. We use AI to do what AI is good at (the volume code conversion), and senior engineers do what they're good at: the architecture decisions, the edge cases, the rollback plans. The result is a migration that runs in months, not years, with zero production downtime.

What you get

Deliverables, not promises.

Every engagement ships these artefacts. Nothing here is fluff. Each item is something your team will hold in their hands at the end.

Migration plan + risk register

Phased plan with explicit rollback triggers at every cutover boundary.

AI-assisted code conversion

Agents do ~70% (boilerplate, conversions). Senior eng reviews + handles edge cases.

Test suite migration

Coverage is maintained. Tests are ported and verified before the underlying code is touched.

Strangler-pattern rollout

Old and new run in parallel; traffic shifts gradually behind feature flags.

Data migration scripts

Idempotent migration scripts with dry-run mode and full rollback paths.

Cutover + decommission plan

A scheduled cutover with a rehearsal, then decommission of the legacy system.

How we work

The process, step by step.

No mystery, no consultant theatre. This is how the work actually flows from kickoff to handover.

  1. Step 1

    Audit current system

    Map dependencies, integration boundaries, data ownership, deployment surfaces.

  2. Step 2

    Migration + rollback plan

    Design phased migration with explicit rollback triggers. Stakeholder sign-off before we touch code.

  3. Step 3

    AI converts, humans review

    Agents handle the volume conversion. Every module gets a human review before merge.

  4. Step 4

    Migrate tests, prove parity

    Tests port first, then the code. The migration is "done" when tests pass on both old and new.

  5. Step 5

    Strangler rollout

    Gradual traffic shift, feature flags, monitoring. Rollback in one config change if needed.

  6. Step 6

    Cutover + decommission

    Scheduled cutover after a rehearsal. Legacy decommissioned only after a watching period.

Our approach
~70%
Of conversion work done by AI

A real example: a React 16 → 19 migration of a 400k-line clinical platform that took 14 weeks instead of the estimated 9 months, roughly 3× faster than the hand estimate. Senior eng on architecture; agents on conversion. We have applied the same approach to language, database and cloud migrations; ask for the example closest to your stack.

FAQ

The questions that actually come up.

Framework upgrades (React 16→19, Angular 8→18), language ports (Ruby→TypeScript, .NET Framework→.NET 9), cloud (on-prem→AWS/GCP/Azure), database (MySQL→Postgres, MongoDB→Postgres), monolith→services.

Ready to scope AI-Assisted Migrations?

A 30-minute call. We map your situation against the engagement, give you a real estimate, and tell you honestly whether we are the right team for this.

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