Incrementally decompose your monolith into well-bounded modules, without halting feature delivery or risking a costly rewrite.
Your monolith was the right call at launch. But invisible coupling has accumulated, and every change is now a gamble.
We analyse your codebase, data flows, and team structure to identify natural module boundaries. No code changes, just a clear picture of where coupling hurts most.
We define bounded contexts aligned to your business capabilities, not arbitrary technical layers, and validate them against real feature requests.
We work alongside your teams to extract the first two modules, establishing patterns your engineers replicate for everything that follows. Monolith and new modules run side by side.
Dependency graphs, coupling hotspots, data ownership conflicts, and a risk-rated component list, written for both technical leads and executive stakeholders.
ReportA visual and documented breakdown of proposed bounded contexts, public contracts, ownership, and inter-module communication patterns. The blueprint for every future extraction.
DiagramA quarter-by-quarter plan prioritising modules by business impact and extraction complexity, with effort estimates, risk mitigations, and clear milestones leadership can track.
RoadmapThe first two extracted modules, fully tested and running in production, complete with event contracts, CI pipelines, and monitoring, as the template for all subsequent work.
CodeNo. Every extraction is incremental and feature-flagged. The monolith and the new modules run side by side, so feature delivery continues uninterrupted throughout the engagement.
The assessment delivers actionable insight in 2–3 weeks. The first extracted module typically lands in production within 8–12 weeks, and your team takes the pattern from there.
We embed with your engineers. The goal is capability transfer, not consulting dependency, your team owns the codebase and the pattern library when we leave.
The patterns are framework-agnostic. We've modernised monoliths across Symfony, Laravel, and plain PHP, the approach translates cleanly to any codebase with clear seams.
We map data ownership as part of the assessment and extract schemas in the same incremental way, private tables per context, event-carried state for cross-context reads, and a clear strangler migration plan for legacy shared tables.