“I very much respect the knowledge that you have. You have a lot of things, just in our few communications, that no one else has mentioned. No one else has even made me think about them.”
Legacy Modernization
Replace the old system while it keeps running
We take aging codebases onto a supported, maintainable stack without betting the company on a rewrite. The old system keeps running while we replace it one proven seam at a time.
Why choose us for legacy modernization?
A system that still pays the bills gets replaced one seam at a time, with a test that proves each move and a rollback that has been rehearsed.
Incremental migration plan
A seam-by-seam roadmap keeps the current system running while modern capabilities replace it in production, so your product team keeps shipping through the whole programme.
Characterization test harness
Golden-master and contract tests capture what the legacy system actually does before we change its internals, so a changed output is caught by an alarm rather than by a customer.
Supported modern stack
End-of-life frameworks, runtimes and build tooling are replaced with a maintainable baseline your team can hire for, chosen for operational fit rather than novelty.
Safe data migration
Backfills, dual writes, shadow reads and reconciliation checks run before any old data path is retired, so the new store is proven consistent before it becomes authoritative.
Stable integration boundaries
Adapter APIs and anti-corruption layers stop new services inheriting old-system assumptions, so each capability you move out is genuinely free of the one it left.
Reversible cutovers
Feature-flagged releases, parallel-run windows, observability and a rehearsed rollback go with every migration step, so no cutover is a one-way door.
What we build in legacy modernization
The moves an aging system needs, each made while the old path still serves traffic.
Monolith to services
Capabilities extracted into separately deployable services, only where the operational case is real.
- Facades in front of each capability before extraction
- Contracts and data ownership agreed per service
- Both paths kept running until the switch is proven
Framework upgrades
End-of-life frameworks and runtimes brought onto supported versions, one jump at a time.
- Characterization tests written before the first jump
- Dependencies and deprecated APIs replaced along the way
- Each version step deployed and verified in production
Database migrations
Schema and engine moves reconciled before the old store is retired.
- Backfills run in batches while the system stays live
- Dual writes and shadow reads to prove parity
- Reconciliation reports before the cutover is called
UI replatforming
Legacy front ends moved onto a modern framework, one screen at a time.
- Routes that switch per page between old and new
- Shared session, auth and styling across both stacks
- Design system components reused as screens migrate
Strangler-fig rewrites
A new system grown around the old one, seam by seam.
- A routing layer that decides which system answers
- Each seam taken over and verified before the next
- Legacy paths retired once nothing depends on them
On-prem to cloud
Phased moves to AWS, GCP or Azure with an explicit cutover plan.
- Dependency mapping across servers, jobs and integrations
- Dual-running with data transfer and validation
- Cutover rehearsed, with a way back if needed
Recent products we shipped
Our most recent case studies. Each result is the one its own case study reports, in its own words.
30+ SKUs scanned into one Shopify draft order; the old version choked on large ones.
Draft Deputy
Shopify · Micro-SaaS
1,000+ skincare formulas resolved from a 60-second phone scan in 55+ San Pablo pharmacies, before the customer leaves the store.
2250
A.I · Custom Web App

3.5K students stayed online while a Lovable-built front end was mapped onto the live LMS.
Squid Academy LMS
SaaS · Custom Web App

Non-marketers launch Meta and TikTok campaigns from one plain form, and read both platforms’ results in one view instead of two ad managers.
AI Agent for Meta and TikTok Ads
MVP · SaaS
How we build legacy modernization
Four stages, from mapping the system to removing the dead code once the new path owns the traffic.
Map the system and the risk
We audit architecture, dependencies, data ownership, deployment paths, failure modes, and the areas nobody wants to touch.
Build the safety net
Characterization tests, observability, and stable boundaries go in before migration work starts. We need to detect changed behaviour, not hope for it.
Migrate one seam at a time
Each capability moves behind a facade, runs alongside the legacy path, and proves itself on real traffic before cutover.
Cut over and remove dead code
After reconciliation and a rollback rehearsal, traffic moves to the new path and the old one is decommissioned so the system genuinely gets smaller.
- See our full process
What clients say after the build
Real client reviews, every one checkable at source.
Legacy modernization questions
The practical questions teams ask before letting anyone touch a system that still pays the bills.
Incrementally, by default. Big-bang rewrites freeze feature work and put the whole programme behind one high-risk cutover. We use strangler-fig and branch-by-abstraction patterns so the product stays releasable. A full rewrite is occasionally the right answer; the initial audit tells us when.

