Legacy System Modernization
Move off old systems without downtime. We refactor, migrate to cloud, modernize the database, and keep every row of your data intact.
On a legacy system
- Software so old nobody wants to touch it
- Security patches stopped years ago — you're one breach away
- Integrations impossible because the APIs don't exist
- The one person who understands it retires next year
After modernization
- Modern, maintainable stack on current frameworks and runtimes
- Security patches flowing automatically, audit logs built in
- Clean APIs that talk to the rest of your tool stack
- Documentation and multiple developers who can maintain it
How We Build It
Archaeology
We reverse-engineer the legacy system — data model, business rules, hidden logic in stored procedures and triggers. Nothing gets lost because we didn't look.
Target Architecture
We design the replacement: modern stack, cleaner data model, proper APIs. You sign off on the blueprint before migration work begins.
Strangler Pattern
We incrementally replace the legacy system module by module, routing traffic to the new one as each piece proves stable. No big-bang cutover.
Data Migration & Testing
Scripted migrations with full reconciliation. Every record verified. We run parallel systems until the numbers match exactly.
Cutover & Decommission
Final cutover during a maintenance window, legacy system kept cold for 90 days as a safety net, then decommissioned once you're confident.
What You Get
- Fully migrated application on a modern, supported stack
- Complete data migration with reconciliation reports
- API layer exposing business logic to the rest of your tools
- Documentation of the new architecture and business rules
- Runbook for operating and extending the new system
- 90-day parallel-run period with rollback plan
Frequently Asked Questions
How do we avoid downtime during the migration?
We use a strangler-pattern approach. Old and new systems run in parallel, traffic gradually shifts to the new one module by module, and the old stays online as a safety net for 90 days after cutover.
What if critical business logic is trapped in stored procedures nobody documented?
Normal. The archaeology phase reverse-engineers those procs, verifies behavior against real data, and rewrites them into application code or modern equivalents. Nothing ships until the numbers match exactly.
How do you handle data migration with years of historical records?
Scripted ETL with row-count and checksum reconciliation. Every record is verified. For large datasets we do incremental migrations during low-traffic windows so nothing times out.
What's a realistic timeline?
Small apps 8 to 12 weeks. Mid-size systems 3 to 6 months. Large multi-module platforms 6 to 12 months, broken into phased releases you can review and course-correct.