Legacy Application Modernization Services, Delivered Faster with AI
Modernize the legacy systems your business still runs on, in less time and at lower cost. AI accelerates the heavy lifting, senior engineers own every decision, and a test suite built from your own business rules proves nothing broke. Costed, reversible increments with zero operational disruption.
ISO 27001 Certified
Oracle Partner
SnowflakePartner
AWS Partner
For CIOs and CTOs Who Own a System Nobody Wants to Touch
Your legacy application runs, but its hidden costs drain your budget. The CIO sees mounting technical debt; the CTO sees a blocked roadmap. Most teams delay legacy software modernization for the same two reasons: it looks slow, and it looks expensive.
GrowExx removes both objections. We assess your estate, assign each application a costed disposition and sequence the migration so you see the ROI before a single line of code changes, then use AI-assisted engineering to deliver each increment in a fraction of the traditional time.
The Three Layers of Legacy Application Modernization
Uptime holds and the vendor still answers, which keeps the true exposure off the board agenda.
That the rules are documented, the code is readable and the dependencies are supported. In reality, no one has checked
Business rules extracted into automated tests, a costed per-application plan and a fully reversible migration path under ISO 27001-certified processes.
AI-Assisted Speed. Senior-Engineer Judgment. Test-Proven Safety.
Traditional modernization is slow because people read millions of lines of undocumented code by hand. AI now does much of that reading, drafting and testing. It does not make decisions about your core systems. Senior engineers working to GrowExx engineering standards do, and every AI-produced change must pass the regression suite built from your business rules before it goes near production.
What AI acceleratesParses source, job schedules and schemas to map dependencies and undocumented integrations
What a senior engineer ownsValidates the map with your team and signs off the risk register
What AI acceleratesDrafts business rules and edge cases from COBOL, PL/SQL, RPG or VB6 in plain language
What a senior engineer ownsConfirms each rule with your domain owners and converts it into an executable test
What AI acceleratesScores code complexity and test coverage per application to inform estimates
What a senior engineer ownsAssigns disposition, cost and sequence, and defends it to your board
What AI acceleratesGenerates translation drafts, scaffolding and test cases for the target stack
What a senior engineer ownsDesigns the architecture, reviews every pull request, runs the parallel comparison
What AI acceleratesGenerates documentation, runbooks and architecture records from delivered code
What a senior engineer ownsReviews accuracy, trains your team and signs the decommissioning plan
Faster to a costed roadmap
AI-assisted code analysis means the full estate assessment and costed roadmap arrive in 2–4 weeks, not a quarter.
Lower cost per increment
Smaller senior teams deliver more because AI handles repetitive reading, translation and test writing. Typical reduction in delivery effort: 30–50% versus manual modernization.
No black-box code
Every AI output is reviewed, versioned and tested. Your code stays in your environment or an approved private model deployment and is never used to train public models.
How we govern AI across delivery: AI-driven development → · How we verify AI-written code: AI code audit & cleanup →
Our Legacy Application Modernization Services
Six services that cover legacy system modernization end to end, from the first assessment to decommissioning. Fund one, or sequence them as a program.
Estate Assessment & Roadmap
A functional dependency map of your applications, scored by risk, cost and criticality. Each system gets one of six modernization paths with exact costs, sequence, and unblocked roadmap milestones. An actionable blueprint, not a slide deck.
Code Refactoring & Rule Extraction
Senior engineers, assisted by AI code analysis, extract undocumented business rules, edge cases and pricing logic and turn them into automated tests, so the new system is verified against real-world behavior, not memory.
Monolith to Microservices Decomposition
We break monoliths down by business capability, isolating services behind an anti-corruption layer while core logic stays live. Sometimes a smaller, better-bounded monolith is the right end state, and we will tell you when.
Platform, Database & Cloud Migration
Mainframes, aging .NET estates, and out-of-support databases moved to AWS, Azure, or GCP, chosen on workload fit and license savings. Oracle estates: see Oracle on-premises-to-cloud migration.
Legacy Integration & API Enablement
An API and event-streaming layer over existing systems lets digital channels and AI workloads connect. Nightly batches become real-time data, unblocking your roadmap months before core replacement.
Technical Debt & Run-Cost Management
A metrics-driven program that cuts infrastructure spend and deployment failures. Every quarter we retire specific debt items and measure the financial impact your CIO can take to the budget review.
Legacy Modernization, Matched to How Your Industry Operates
A legacy system creates a different kind of liability in every sector. Four modernization playbooks, one method.
The Challenge
Core banking ledgers run on decades of undocumented COBOL. As the engineers who maintain them retire, every regulatory update turns into forensic work.
How We Help
AI-assisted extraction of rules from COBOL and PL/SQL into automated tests, verifying compliance before any code changes. Core systems placed behind real-time APIs to remove nightly batch dependencies.
Deliverables
Core system dependency maps, rule catalogs with automated tests and real-time API layers over systems of record.
Quantified Result
Product launch and configuration cycles
The Challenge
Plant systems on IBM i, VB6 or old .NET depend on 2 AM flat-file transfers. Upgrades keep slipping because downtime risk outweighs the visible maintenance cost.
How We Help
We design around your existing maintenance windows, convert flat-file transfers into real-time events, then rehost legacy applications first to remove platform risk without disrupting operations.
Deliverables
Plant interface maps with downtime constraints, file-to-event streaming blueprints and rehost schedules.
Quantified Result
Across 4 core plant interfaces with zero downtime
The Challenge
On-premise databases past end of support and legacy HL7 interfaces create serious HIPAA exposure. Unpatched legacy infrastructure is a common breach entry point.
How We Help
We map protected health information (PHI) flows and modernize the highest-risk dependencies first, moving HL7 v2 interfaces to secure FHIR APIs under ISO 27001-certified processes, with ISO 13485 coverage.
Deliverables
PHI data flow maps, unsupported dependency registries and verified HL7-to-FHIR migration plans with compliance packs.
Quantified Result
To a complete PHI flow map and HIPAA risk registry
The Challenge
Commerce monoliths turn peak season into a high-risk event because catalog, pricing and checkout share one release train. Finance runs on spreadsheets beside an unmodernized ERP.
How We Help
We decompose the monolith by capability, carving out high-change features like pricing first, and automate reconciliation directly against your existing ERP without a rewrite.
Deliverables
Capability decomposition maps, anti-corruption layer designs, and ERP reconciliation automation.
Quantified Result
AP close, 99% invoice match accuracy, 100+ store retailer
Cut AP close from 20 days → 2 without replacing the ERP.
The assessment, the sequence and the numbers, walked through end to end. 20 minutes. No slides.
Five phases that turn an unmeasured liability into a costed, reversible program
Click any step to see what happens inside it and what you receive.
We inventory applications, interfaces, batch jobs, data stores and infrastructure, then trace what actually calls what, including undocumented integrations. Coverage includes COBOL and mainframe, IBM i and RPG, Oracle Forms and PL/SQL, VB6 and Delphi, .NET Framework, legacy Java and AngularJS.
Output: Dependency map, run-cost baseline, and risk register, agreed with you before any code changes.
Senior engineers read the legacy code for the rules the business still relies on and convert them into executable tests. This is the step most rewrites skip, and the reason most rewrites fail acceptance: without it, the only specification is the system you are replacing.
Output: Rule catalogue and regression suite that both the old and new system must pass.
Every application receives a disposition (retain, rehost, replatform, refactor, rearchitect or replace) with a fix cost, a run-cost saving and a plain-language cost of inaction. Your board approves the sequence in one meeting and funds one increment at a time.
Output: Per-application disposition, costed increment sequence and payback model.
Traffic routes through a façade so capabilities move one at a time while the legacy system keeps serving everything else. Each increment runs in parallel against the Step 02 suite before taking live traffic. Targets include .NET 8, Java 21, Node.js, Python, React and Angular on AWS, Azure or GCP, with Kubernetes, Kafka, PostgreSQL and Snowflake where justified.
A legacy system that is still switched on is still costing money, so decommissioning is a tracked deliverable. We measure run cost against the Step 01 baseline, retire what has been replaced and hand over documentation, tests and pipelines to your team.
Output: Decommissioning certificate, measured run-cost movement and full technical handover.
Why Choose GrowExx for Legacy Application Modernization?
AI-Assisted, Engineer-Governed
AI handles reading, drafting and test generation; senior engineers own architecture and every merge. AI speed without handing your core systems to AI.
Platform-Neutral Alignment
We receive no vendor payouts. Your target platform follows your workload profile and licensing limits, even if that means keeping your current system.
Rules Extracted Before Code Changes
Unwritten logic becomes automated tests before anything is rewritten. Your team inherits a verified regression suite, not a folder of assumptions.
ROI Defended Up Front
Every system gets a fixed cost, a run-cost saving and a cost of inaction before kickoff. You approve discrete increments on numbers, not open-ended contracts.
Audit-Grade Governance
Backed by ISO 27001 and ISO 9001 and ISO 13485 certifications. Architectural changes produce evidence mapping to SOC 2, HIPAA and GDPR controls.
Reversible Increments, Full Handover
Each phase stands alone and delivers value. You own the rule catalog, tests and pipelines, with no licensing fees, hidden dependencies or mandatory retainers.
Explore how our legacy modernization services can help
Legacy Modernization Case Studies
What a costed, incremental programme returns — and what standing still costs.
Real-Time APIs Over a COBOL Core Ledger, Without Touching the Ledger
Every new product required changes to 40-year-old COBOL that only two remaining engineers understood.
- AI-assisted extraction of interest, fee and posting rules into 1,800+ regression tests
- Read and write APIs over the ledger via an anti-corruption layer
- Product configuration moved into a governed rules service
Stack: COBOL, DB2, Java 21, Kafka, AWS
From Nightly Flat Files to Real-Time Events Across Four Plant Interfaces
Production, inventory and ERP synced through nightly files. A failed batch meant a morning of manual reconciliation.
- Every interface mapped against existing maintenance windows
- File transfers replaced by event streams one at a time, with parallel runs
- RPG workloads rehosted first to remove platform risk
Stack: IBM i, RPG, Kafka, .NET 8, Azure
A PHI Flow Map and HIPAA Risk Registry in 21 Days
An end-of-support database and a mesh of HL7 v2 interfaces carried PHI through systems nobody had fully mapped.
- AI-assisted parsing of interface definitions and schemas to trace every PHI flow
- Unsupported dependencies ranked by exposure and remediation cost
- Sequenced HL7 v2 to FHIR plan with compliance validation pack
Stack: SQL Server 2012, Mirth, HL7 v2, FHIR R4
AP Close Cut to 2 Days Without Replacing the ERP
Invoice matching ran on spreadsheets beside an aging ERP, and errors surfaced late in the close.
- Recogent deployed over the existing ERP for matching and anomaly detection
- ERP kept as system of record; no core changes
- Live in under 4 weeks with rules handed to finance
Stack: Existing ERP, Recogent, Snowflake
The CFOs and CIOs we've worked with.
GrowExx is the only partner who refused to start coding until we agreed on the ROI math. That discipline is exactly why our reconciliation agent shipped on time, on budget.
We had three AI vendors. Two showed us demos. GrowExx showed us the eval harness, the cost-per-task dashboard, and the rollback plan. That's why they got the contract — and the renewal.
Their team treats every agent like a regulated piece of software, not a science project. That's the difference between a pilot you brag about and an agent your auditor signs off on.
Talk to the team behind these outcomes.
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Recogent sits on top of your existing ERP and automates invoice matching and anomaly detection across AR, AP and the ledger. It is the API-first approach on this page in action: modernize the workload, keep the system of record.
Where to go next.
For estates where the newer code was AI-generated and nobody has verified what is in it before it becomes the next legacy system.
For teams running modernization and new product work in parallel, with AI governed across the full software lifecycle.
For leaders deciding where AI belongs in the modernized estate, with the business case priced before the work starts.
For estates looking to deploy secure, private AI workloads directly over legacy data structures without breaking core transactional logic.
