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Legacy systems are rarely called "legacy" internally — they're called "the system." And the system works. It processes orders, manages records, generates reports. But it's slow to change, expensive to maintain, and increasingly dependent on engineers who remember why something was built a certain way twelve years ago.
Full codebase assessment: architecture, code quality metrics, dependency health, test coverage, and documentation. Outputs a prioritized list of what to address and in what order.
A phased plan that sequences modernization work to minimize disruption and deliver incremental value — not a big-bang replacement schedule.
Phase-by-phase delivery — refactoring, API additions, database migration, framework upgrades — with regression testing at each stage to ensure stability.
Bring us the constraint. We'll bring the team.
The instinct is to replace it entirely. The reality is that a complete replacement is one of the highest-risk software projects any organization can undertake. The business logic embedded in a legacy system — the edge cases, the compliance rules, the exceptions to the exceptions — is nearly impossible to fully capture in a requirements document. Rebuilds often reproduce the original system's problems with a newer technology stack.
We take a different approach: structured modernization, applied incrementally.
We begin every modernization engagement with a thorough assessment: code quality, architecture patterns, dependency health, test coverage, documentation state, and the specific pain points that are driving the modernization need. This produces a prioritized remediation backlog — not a rewrite plan.
We apply the Strangler Fig pattern and other incremental migration strategies to replace and improve parts of the legacy system without disrupting the whole. New capabilities are built alongside the legacy system; traffic migrates gradually; the legacy components are decommissioned when their replacements are proven.
Many legacy systems have no integration capability because they were never designed for it. We add a clean API layer that exposes the system's data and functions to modern integration patterns, without rewriting the underlying logic.
Legacy databases often have schema designs that reflect how the system was originally built, not how the business currently operates. We plan and execute database schema migrations — including data transformation and validation — as part of modernization engagements where the data model is a primary bottleneck.
Outdated frameworks and dependencies accumulate security vulnerabilities and compatibility issues. We manage upgrade paths for major framework versions with proper testing coverage to ensure stability through the transition.
We produce architecture documentation for everything we touch and transfer knowledge to the team who will maintain the modernized system going forward.