Your Legacy Code is a
Ticking Time Bomb.
You are sitting on 15 years of technical debt. We modernize aging mission-critical systems using AI-Accelerated Refactoring. Move from Monolith to Microservices before the past drags you down.
public class Monolith extends Legacy {
private void init() {
// TODO: Fix memory leak
system.crash(ALWAYS);
security.patch(NULL);
}
}
Why "Do Nothing" is
Not an Option.
Maintaining legacy systems isn't free. It's a compound interest debt that grows every day. You are one patch away from a critical failure.
The Talent Cliff
Avg Dev Age: 55+
The developers who wrote your core logic are retiring. Hiring for COBOL, old Java, or Perl is nearly impossible and exorbitantly expensive.
Unpatchable Security
CVEs Detected: Critical
Your libraries are 10 years old (e.g., Log4j vulnerabilities). You can't patch them because upgrading breaks the entire monolith.
Feature Paralysis
Lead Time: 6 Months
Fear of breaking the "Spaghetti Code" means simple changes take months. Your competitors are shipping weekly while you are stuck testing.
Don't Rewrite. Strangle.
"Big Bang" rewrites fail 70% of the time. We use the Strangler Fig Pattern. We build the new system around the edges of the old one, intercepting traffic and replacing features one by one until the monolith dies of natural causes.
Stage 1: As-Is
All traffic hits the legacy app. Code is tightly coupled. High risk of failure on change.
Stage 2: The Strangler
We place an API Gateway in front. New features (e.g., Auth) are routed to Microservices. Old features stay on Legacy.
Stage 3: To-Be
The monolith is decommissioned. You now run a scalable, containerized architecture. Zero Downtime achieved.
if (region == 99) ...
If Region is '99', apply
global tax exemption.
Decode the Past.
Instantly.
The biggest risk in migration is "Knowledge Loss." The developers who wrote the code are gone. We use LLMs to analyze your entire repository, extracting hidden business rules and generating unit tests before we write a single line of new code.
Automated Reverse Engineering
AI scans the monolith and generates plain-English documentation of every business rule, creating a "Spec" that actually matches reality.
Test Case Generation
We use AI to generate thousands of unit tests for the old system. We run these against the new microservices to mathematically prove parity.
From Iron Servers to
Infinite Scale.
We don't just patch your code; we re-platform your business. We move you from expensive, fragile on-premise hardware to resilient, auto-scaling cloud infrastructure.
Containerized (Kubernetes)
No more "it works on my machine." We package every microservice in Docker containers, orchestrated by K8s for zero-downtime deployments.
Serverless & Event-Driven
Pay only for what you use. We implement AWS Lambda or Vercel Edge Functions for bursty workloads, reducing idle server costs by 80%.
Managed Databases
Stop managing backups. We migrate your data to managed Postgres (Supabase/RDS) or distributed SQL (CockroachDB) for instant failover.
De-Risking the Transformation.
We don't guess. We follow a strict, gated migration process. Every phase has a "Go/No-Go" decision point to ensure business continuity.
Discovery & Scan
We deploy our AI agents to map your dependency graph, identify "Dead Code," and document the existing business logic.
- Static Code Analysis
- Dependency Mapping
- Risk Assessment Report
The Pilot (Tracer Bullet)
We migrate one low-risk, vertical slice of the application (e.g., "User Profile") to the new microservices architecture to validate the stack.
- Setup CI/CD Pipelines
- Deploy API Gateway
- Migrate 1st Module
Parallel Running
The "Strangler" phase. We run the new system alongside the old one. Traffic is shadowed to both to ensure 100% data parity.
- Traffic Shadowing
- Data Consistency Checks
- Gradual User Shift (10% → 100%)
Cutover & Sunset
Once the new system is stable, we turn off the legacy servers. Your technical debt is officially paid off.
- Decommission Hardware
- Archive Legacy Data
- Full Modernization
The "Hardest Part"
Handled Perfectly.
We don't just "lift and shift" your messy data. We run a rigorous ETL (Extract, Transform, Load) process. We scrub duplicates, normalize schemas, and validate every single row before it touches the new system.
Schema Normalization
We fix your technical debt at the data layer. We convert messy, redundant tables into strict, relational schemas (3NF) optimized for modern queries.
Dual-Write Parity
During the transition, we write data to both the old and new databases simultaneously. We run automated diffs to ensure 100% consistency.
The "Rewrite" Trap vs.
The AI Advantage.
Most modernization projects fail because they rely on armies of developers manually rewriting code. We replace "Brute Force" with "Machine Intelligence," cutting timelines by 60%.
Manual Rewrite
"The Army of Consultants"
- ❌ High Risk: Manual translation introduces human error.
- ❌ Knowledge Gap: Junior devs guessing logic.
- ❌ Incentive Misalign: They profit when it takes longer.
AI-Accelerated
"Smart Agents + Senior Architects"
- ✅ Zero Guesswork: AI extracts logic 1:1.
- ✅ Auto-Testing: 100% test coverage generated instantly.
- ✅ Fixed Scope: We profit by finishing fast.
Technical FAQ.
Answers to the most common questions CIOs ask about risk, timeline, and the "Strangler Fig" methodology.
Why shouldn't we just "Lift and Shift" to the cloud?
"Lift and Shift" (Rehosting) solves nothing. It simply moves your spaghetti code from an on-premise server to a cloud server. You still have a monolith, you still have security vulnerabilities, and you now pay higher cloud fees. We believe in Refactoring—breaking the code into microservices to actually fix the underlying architecture.
What is the "Strangler Fig Pattern"?
The Strangler Fig Pattern is a migration strategy where we incrementally replace specific functionalities of the legacy system with new microservices. The two systems run in parallel. Eventually, the new system grows to encompass all features, and the old system is "strangled" (decommissioned) with zero downtime.
How much does legacy modernization cost?
Costs vary based on lines of code (LOC) and complexity. However, the "Cost of Doing Nothing" is typically higher due to maintenance fees, security breaches, and lost agility. Our AI-accelerated approach typically reduces the standard migration cost by 40-60% compared to manual rewrites.
Can AI really understand our custom legacy logic?
Yes. LLMs (Large Language Models) excel at translating rigid languages like COBOL, Fortran, or older Java/PHP versions. We use AI to reverse-engineer your business rules into plain English documentation first, which your team verifies before we generate the new code.
How do you prevent data loss during migration?
We use a "Dual-Write" strategy. During the transition, data is written to both the old database (Oracle/SQL Server) and the new cloud database (Postgres) simultaneously. We run automated integrity checks to ensure 100% parity before switching off the old source.
How long does a typical migration take?
Instead of a 3-year "Big Bang" project, we deliver value in 3-6 month phases. We start with a low-risk module (Pilot) to validate the stack, then migrate high-impact modules iteratively. You will see your first microservice live within 90 days.
Will the new system be SOC2 / HIPAA compliant?
Yes. We build "Security by Design." Unlike legacy apps with hardcoded passwords, we implement modern OAuth2 Identity Management (Auth0/Okta), encryption at rest (AES-256), and TLS 1.3 in transit, making your new system audit-ready immediately.
What happens to our existing IT team?
They evolve. We work with your team. As we modernize the stack, we upskill your existing developers on modern technologies like React, Node.js, and Kubernetes, turning your maintenance team into an innovation team.
The Future is Waiting.
The Past is Costing You.
Don't wait for a critical failure to force your hand. Book a Codebase Assessment today. We'll deploy our AI agents to scan your repo and give you a fixed-price modernization roadmap.