Modernize applications holding the business back and preserve those that still work.
Legacy systems rarely fail all at once. They slow you down gradually, with every release taking longer, every integration needing more custom work, and every change carrying more risk. Over time, the system meant to support the business ends up limiting what it can do next.
Too much time and budget goes into keeping the current system running instead of improving the product or supporting growth.
Releases are too slow and too risky. Even small changes take more coordination, testing, and effort than they should.
We know technical debt is holding us back, but we don’t know what needs to be fixed first or where the investment will have the biggest impact.
Connecting new products, partners, or systems takes too much custom work and slows down new initiatives.
Our current technology is becoming harder to support, and we’re increasingly concerned about security, compliance, and operational risk.
We depend too heavily on a few people who understand how the system works. If that knowledge disappears, making changes becomes even riskier.
Our legacy systems are slowing down cloud, data, automation, and AI initiatives because the information and functionality we need are difficult to access.
We know we need to modernize, but we don’t want a costly rewrite or a major disruption to the business.
Before we invest, we need a clear view of what should stay, what should change, and what will deliver the most value.
From understanding what you have today to rebuilding for the cloud, we offer focused services that tackle modernization one priority at a time. Choose the approach that fits your goals, budget and risk tolerance, and we’ll take it from there.
We partner with ambitious organizations to solve complex problems, craft meaningful experiences, and deliver measurable results.
Strategic re-architecting and data modernization fueled FinQuery’s next wave of growth
Brightree modernized its legacy platform with KMS, boosting scalability and enabling an $800M acquisition.
Proem’s shift to microservices with KMS unlocked faster releases, better performance, and room to scale.
Modernization works best when every decision is based on a clear understanding of the system and every change is tested before it goes live. Our five-phase process takes you from a full assessment to a production-ready system, delivering in manageable stages so your business keeps running while the technology moves forward.
Assessment report
Risk map
Prioritized modernization candidates
Target architecture
Modernization strategy
Business and technical priorities
Implementation roadmap
Migration plan
Testing and rollback strategy
Modernized components
Automated tests
Integrations
Migrated workloads
Documentation
Monitoring and observability
Handover
Optimization backlog
Legacy modernization spans architecture, application engineering, data, cloud infrastructure, quality engineering, and systems integration. KMS brings those disciplines together in one program, tied to the system’s actual business constraints
Select your industry to explore tailored Legacy Modernization.
Financial platforms often have to modernize without compromising transaction integrity, security, uptime, or existing customer workflows.
Moves core financial systems to cloud or hybrid environments through a phased approach, not a single high-risk cutover.
Reduces technical debt in transaction-critical systems without discarding the business logic that still works.
Modernizes how financial data is stored, moved, and exposed to support real-time reporting, auditability, and compliance requirements.
Connects core financial systems to payment networks, partners, and regulatory reporting tools through defined interfaces.
Healthcare modernization combines technical complexity with requirements around sensitive data, availability, and regulatory processes.
Restructures existing code and architecture to improve maintainability, performance, and modularity without discarding the business logic that still works.
Modernizes how clinical and patient data is stored, moved, and exposed when the existing data layer limits security, integration, or analytics.
Enablement Builds the CI/CD, automated testing, and monitoring needed to maintain uptime and traceability throughout regulated releases.
Improves clinician- and patient-facing interfaces without rebuilding the entire backend at the same time.
SaaS and technology companies often modernize while simultaneously supporting active users, product releases, and continued scale.
Enablement Builds the CI/CD, automated testing, and monitoring needed to keep the platform reliable through continuous releases.
Moves workloads to cloud or hybrid environments when doing so creates a clear technical or business advantage at scale.
Modernization Introduces modern APIs and integration layers to support partner ecosystems and developer integrations.
Modernization Uses AI to analyze legacy source code and validate functional parity as codebases grow, with engineers retaining final sign-off.
Manufacturing systems often combine decades-old plant-floor software with the ERP and supply chain platforms the rest of the business depends on.
Assesses business value, architecture, and risk across plant-floor and ERP systems to decide what to retain, refactor, or replace.
Connects legacy MES and ERP systems to modern supply chain, logistics, and IoT platforms through defined interfaces.
Modernizes how production and equipment data is stored and exposed so it can be used for analytics and reporting.
Restructures production-critical systems to improve maintainability without discarding the business logic that still works.
Retail and e-commerce platforms have to modernize while handling seasonal traffic spikes, tight margins, and a growing number of sales channels.
Moves storefront and backend workloads to cloud or hybrid environments capable of handling peak-load traffic.
Modernization Connects legacy commerce platforms to marketplaces, payment gateways, and fulfillment or logistics partners through defined interfaces.
Modernizes storefront and checkout experiences without rebuilding the entire backend at the same time.
Modernizes how inventory, order, and customer data is stored and exposed to support real-time visibility and personalization.
Legal organizations need to modernize case management and document systems without disrupting active matters or chain-of-custody requirements.
Restructures existing case management and document systems while preserving the business logic that still works.
Modernizes how case, client, and document data is stored and exposed to improve search and access.
Enablement Builds the automated testing and monitoring needed to keep systems auditable and reliable through ongoing changes.
Aviation systems often combine safety-critical operations with legacy reservation, scheduling, and ground systems that cannot tolerate unplanned downtime.
Roadmap Assesses architecture, dependencies, and risk across operational systems before any modernization work begins.
Connects legacy reservation, scheduling, and operations systems to modern partner and airport systems through defined interfaces.
Modernizes how flight, crew, and operational data is stored and exposed to support real-time use.
Enablement Builds the automated testing and monitoring needed to validate changes without risking the uptime of safety-critical systems.
Engineering time shifts away from workarounds and undocumented dependencies and back into building new capability, instead of just keeping the current system running.
Decoupling removes the cross-component coordination and manual testing that turn routine changes into high-risk releases, so updates ship faster and with less risk.
A modernized application and data layer removes the capacity and responsiveness limits of outdated architecture, so the system can absorb more users, transactions, or data without added strain.
Running on supported frameworks and libraries means vulnerabilities can be patched and compliance evidenced, instead of accumulating as the stack falls further out of vendor support.
Stable APIs replace one-off custom integration work, so connecting a new partner, product, or channel no longer requires a dedicated project each time.
Data and functionality become accessible through controlled interfaces instead of trapped behind legacy systems, so analytics, automation, and AI initiatives can actually use them.
We don’t treat age as a reason to modernize something.
The assessment looks at where the current system is creating measurable cost, delivery constraints, operational risk, or dependency problems, and weighs that against the business value of the application and the complexity of changing it.
The result is a clear view of what needs intervention, what can stay as it is, and where a targeted change is enough. Modernization starts from that evidence, rather than from a predefined scope.
That’s one of the problems the discovery phase is designed to solve.
VELOX, our agentic AI orchestration platform designed for the software development lifecycle (SDLC), can analyze the source code directly to help reconstruct architecture, requirements, dependencies, and business logic that may no longer be documented anywhere else.
That means the project doesn’t depend entirely on outdated documentation or on locating the person who originally built a particular component.
Engineers still validate what VELOX surfaces, but they start with evidence from the system itself instead of rebuilding that understanding manually from scratch.
No.
The work is structured around decision points. You can assess the current system before deciding what should change, review the target architecture before implementation begins, and define the migration and rollback approach before anything is moved into production.
So the commitment becomes more specific as the technical uncertainty comes down, rather than asking you to approve a large modernization scope before the system has been properly understood.
We compare legacy and modernized behavior and use automated regression testing to verify functional parity before cutover.
VELOX helps identify differences between the two implementations, while engineers review anything that could indicate a change in expected behavior.
That matters especially in legacy systems where important business rules may exist in the code without being clearly documented anywhere else.
The engineers.
VELOX can analyze the codebase, reconstruct missing context, surface dependencies, and flag differences between legacy and modernized behavior. It does not approve architecture decisions or production releases.
Technical decisions, exceptions, and final sign-off stay with the engineering team. AI is used to reduce the manual analysis required to get there.
Because replacing everything also means replacing the parts that already work.
A mature legacy system can contain years of business rules, integrations, exceptions, and operational knowledge. Rebuilding all of that introduces a much larger surface area for regression and usually requires the old and new systems to coexist during the transition.
Our approach is to identify the parts creating the problem and change those deliberately, instead of making a full rewrite the default.
Cloud migration changes where an application runs. Application modernization can change how the application is designed, built, integrated, tested, and maintained.
An application can therefore be migrated to the cloud without being substantially modernized, and it can also be modernized without moving to the cloud.
Common approaches include:
- Rehosting: moving an application to a new environment with minimal code changes.
- Replatforming: moving it while adopting selected services or platform capabilities.
- Refactoring: improving the internal code structure without changing its core behavior.
- Rearchitecting: changing the application architecture, for example by separating a monolith into services.
- Rebuilding or replacing: developing a new application or moving the business capability to another product when keeping the existing system no longer makes sense.
Large modernization programs often use different approaches for different applications or components.
Decisions are based on business value, technical condition, operating cost, risk, and dependencies.
Applications that create significant business constraints while offering a manageable modernization path are typically stronger candidates for early phases than systems selected purely because of age.
Yes. Phased modernization can reduce the need for a single high-risk cutover.
Teams can sequence components, validate new and old behavior in parallel, automate regression testing, and build rollback plans around each stage.
The timeline depends on application size and complexity, architectural coupling, data volume and quality, existing documentation and test coverage, compliance requirements, dependencies, and acceptable downtime.
The main cost drivers include application complexity, architecture, dependencies, data migration requirements, existing test coverage, compliance requirements, and the modernization approach selected.
A targeted rehosting or refactoring project typically requires a different level of effort from a full rearchitecture or rebuild.
AI can assist with codebase analysis, architecture documentation, dependency discovery, test generation, refactoring, and behavior validation.
VELOX, for example, can analyze legacy source code where documentation is incomplete and compare legacy and modernized behavior before cutover.
These capabilities accelerate specific engineering tasks; they do not replace senior engineering review or architecture decisions.
No.
Some applications are better refactored, replatformed, or rearchitected within an existing private or hybrid environment, depending on requirements such as latency, regulation, system dependencies, and operational economics.
“KMS collaborates so well with us that they are an extension of our internal team. The code they produce is always well written with good test cases and on-time delivery. If there’s a need for a newer technology, they research and quickly produce a POC to see if it meets our needs.”
“Some 3rd party firms I have worked with in the past have felt like hired hands, but KMS takes a different approach. It is a true partnership. I felt the team was part of our organization and everyone was committed to the success of the project”
Proem’s shift to microservices with KMS unlocked faster releases, better performance, and room to scale.
KMS Technology helped Izenda deliver a modern BI solution that enabled them to achieve an 88% increase in automation coverage.
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