One large, tightly-coupled codebase where every change risks breaking something unrelated.
Interfaces built a decade ago that frustrate users and make onboarding new employees harder than it should be.
Applications built on languages or frameworks no longer maintained or supported by their vendors.
Direct, brittle connections between systems that make every integration change high-risk.
Deployments that take weeks of coordination because nothing in the system is decoupled enough to ship independently.
Every capability exposed through a versioned, documented API before the UI is built on top of it.
Reusable, testable UI components replacing page-by-page legacy templates.
New functionality intercepts and replaces legacy behavior incrementally, not all at once.
Test coverage built against existing behavior before any code changes.
Traffic shifts to the new system in controlled stages with an instant rollback path.
A single source of truth for UI patterns that speeds up every future release.
Every change to the monolith risks breaking something unrelated, so teams avoid touching it at all.
New functionality is built alongside the old system and incrementally takes over, with the legacy system as a safety net.
The application runs on a language or framework no longer patched, maintained, or hireable for.
We plan and execute the migration path off end-of-life technology with minimal business disruption.
Every screen looks and behaves a little differently, built up over years without a shared design language.
A single, reusable component library brings visual and interaction consistency across the whole application.
Direct connections between systems mean a change in one place breaks something unrelated elsewhere.
An API layer sits between systems so each can change independently without breaking the others.
Every release requires coordinating changes across a tangled, monolithic codebase.
Decoupled services and automated pipelines let teams ship independently and more often.
Years of undocumented business rules live only in the legacy code itself.
We capture existing behavior as tests before changing anything, so undocumented logic isn't lost.
Challenge: The client's core policy management system had grown into a 15-year-old monolith so tightly coupled that even minor changes required full regression testing across the entire application, and no one fully understood every dependency anymore.
Approach: Luminogics mapped the monolith's domain boundaries and used a strangler-fig strategy to incrementally extract services, starting with the lowest-risk, highest-value domain, routing traffic to new services while the monolith kept running underneath.
ArchitectureIndependent releases per service instead of full-system regression
Zero disruption to policy operations during migration
Clear domain ownership across engineering teams
Legacy system safely retired one domain at a time
Challenge: The client's internal scheduling application was built on jQuery and page-by-page templates a decade earlier, with every screen looking and behaving slightly differently, making staff onboarding slow and small changes disproportionately time-consuming.
Approach: We built a reusable component-based design system in React, then rebuilt the application screen by screen against it, starting with the highest-traffic scheduling workflows, while keeping the underlying data layer stable throughout.
ArchitectureConsistent interface patterns across every screen
Faster new-employee onboarding on the scheduling system
New screens built in a fraction of the previous time
Improved accessibility compliance across the application
Challenge: The client's field operations app connected directly to their ERP database, so every ERP upgrade or schema change risked breaking the field app with no warning, and adding new integrations meant more direct, fragile connections.
Approach: We introduced an API gateway between the application layer and the ERP, exposing a versioned, contract-first API that the field app and future integrations consume, so the ERP can change underneath without breaking anything built on top of it.
ArchitectureERP upgrades no longer risk breaking the field app
New integrations connect to the API, not the database directly
Versioned contracts make breaking changes visible before they ship
Faster delivery of new field-operations features
An application the team can safely change again
Faster release cycles through decoupled architecture
A modern, consistent user experience
No disruptive big-bang cutover
Undocumented business logic captured as automated tests
Off end-of-life languages and frameworks
Decoupled integrations that survive upstream changes
A reusable design system for future development
Reduced technical debt and security exposure
A platform ready for the next five years, not the last ten
Incremental migration, not big-bang risk
Test coverage before we touch anything
API-first, so systems can change independently
Built for the team that maintains it after we leave
No. We typically use a strangler-fig approach, incrementally routing functionality to the new architecture while the legacy system keeps running, rather than a risky big-bang rewrite.
This is one of the most common starting points for modernization engagements. We assess the codebase, identify what can be migrated automatically versus rewritten, and plan a path off end-of-life frameworks.
Through automated regression test coverage built against the existing system's actual behavior before any code changes, so undocumented rules are captured as tests rather than lost.
Yes. A modern frontend can be layered onto a legacy backend through an API gateway while backend modernization happens incrementally behind it.
An initial assessment and roadmap typically takes 4-6 weeks; full execution is usually 3-12 months depending on the size of the application and whether it's phased incrementally.
The strangler-fig approach is specifically designed to avoid this. Functionality migrates incrementally with the legacy system as a fallback, and cutover happens in stages.
Yes, where it makes sense. A reusable design system ensures consistency across the modernized application and speeds up future development.
Moving to the cloud changes where an application runs; modernization changes how it's built, its architecture, code, and interface. The two are complementary but solve different problems.
