Legacy Machine Migration
Every modernization conversation ends the same way — “too risky, not now.” We built a migration process that removes the bet-everything moment. No big-bang cutovers. No sprint where everything is broken at once. The new system runs live in parallel until it’s proven — the old one doesn’t go dark until you’re ready.
Talk About Your Legacy Stack See pricing →Discovery
Mapping a legacy system by hand takes months — reading undocumented code, tracing data flows, reverse-engineering integrations nobody remembers building. We run AI analysis tools against your codebase and get that work done in days. The dependency map, the technical debt report, the integration inventory — all of it, before we write a line of new code.
We run AI analysis tools against your legacy codebase to map dependencies, identify integration points, and flag technical debt, surfacing what matters in hours instead of weeks of manual review.
Legacy systems are almost never documented. AI generates comprehensive documentation from the code itself: data models, API specs, process flows, and dependency maps, before migration begins.
AI tools validate data integrity during migration, flag schema mismatches, and generate transformation logic for record mapping. Data quality checks that would take weeks to write get generated and run continuously.
AI-generated test suites run the old and new systems in parallel, comparing outputs. Every business logic path gets verified before cutover, not discovered in production after the fact.
How We Run It
Most migration failures happen because of a big-bang cutover, the moment where you flip the switch and hope nothing breaks. We eliminate that moment entirely.
Discovery & mapping AI
AI-augmented analysis maps the full codebase, dependencies, data flows, integrations, undocumented behavior. Produces architecture docs and a risk register before any code is written.
Parallel build
New system is built alongside the legacy system. No production traffic touches the new system until it has verified parity. The old system stays fully operational throughout.
Parity testing AI
AI-generated test suites run both systems against the same inputs and compare outputs. Every business logic path verified. Data migration validated record-by-record before cutover.
Staged cutover
Traffic migrated in stages, not all at once. Canary releases. Feature flags. Instant rollback capability at every stage. No single moment where you can’t go back.
Decommission & handoff
Legacy system decommissioned only after the new system has proven stable under full load. Documentation, runbooks, and architectural decision records handed to your team.
Why AI-Augmented Changes the Timeline
What We Migrate
Aging on-prem infrastructure migrated to Azure or AWS with zero disruption to operations. Lift-and-shift where appropriate; re-architecture where it unlocks value.
NetSuite, legacy WMS platforms. We’ve migrated mid-market operations teams off aging ERP/WMS stacks while keeping warehouses and fulfillment running throughout.
The bespoke application nobody understands anymore. AI analysis maps the undocumented logic; we rebuild it on a modern stack with full test coverage before the old one goes dark.
EDI point-to-point integrations, brittle FTP-based data transfers, hand-rolled middleware. Replaced with event-driven, resilient architectures that don’t break at 2AM.
Years of accumulated data moved and cleaned. AI-validated record mapping, schema transformation, and integrity checking, so you don’t inherit a new system with old data problems.
VB6, .NET Framework 2.x, COBOL, PHP 5, we’ve worked with stacks that should have been replaced a decade ago. AI analysis, modern rebuild, full parity testing.
Technologies we migrate to
Let’s Talk
Most engagements start with a single conversation. Tell us what’s broken, what’s slowing you down, or what you’re trying to build. We’ll give you a straight answer, no pitch deck, no fluff. If we’re a fit, great. If not, we’ll tell you that too.
Start a Conversation →