AI-Led Legacy Modernization for Mission-Critical Postal Operations

Transforming a Legacy Java-Based Operator Workflow into a Modern, Enterprise-Ready Platform

A leading provider of mail processing and postal automation solutions, partnered with Galent to modernize a business-critical operator encoding workflow platform that had become increasingly difficult to maintain and operationally risky.

The platform played a central role in supporting high-volume postal and mail processing operations. However, its dependency on Java Web Start and a tightly coupled legacy J2EE architecture created immediate modernization challenges as enterprise environments evolved beyond legacy Java support models.

The engagement focused on eliminating operational risk, modernizing the application architecture, and accelerating delivery through AI-powered engineering. Leveraging the Galent AI Platform and AI coding agents, the initiative combined deep system discovery, architecture transformation, and spec-driven development to rapidly deliver a fully working modernized solution.

The result: a scalable, enterprise-ready Angular and .NET platform built with modern security, auditability, and operational resilience.

Client Challenges:

Several critical technology and operational challenges emerged:

Java Web Start Deprecation & Operational Risk: The application’s dependency on Java Web Start became a major operational concern after support was removed from Java 11 and modern browsers. This created immediate compatibility, security, and continuity risks for business-critical workflows. .

Legacy Technology Stack & Rising Maintenance Costs: The existing J2EE, JSF, and Swing-based architecture introduced growing technical debt and increasing maintenance complexity. Talent scarcity around legacy Java frameworks further elevated operational costs and long-term sustainability concerns.

Tightly Coupled System Architecture: Direct filesystem integrations, RMI calls, and servlet-based dependencies created a tightly coupled ecosystem that was difficult to scale, modernize, or evolve without introducing operational instability.

Limited Security & Traceability Frameworks: The platform lacked modern authentication, authorization, and audit capabilities, limiting enterprise readiness for future integrations and governance requirements.

Galent’s Approach

We designed and executed an AI-led modernization strategy focused on accelerated discovery, architecture intelligence, and spec-driven engineering./p>

AI-Powered Discovery & Knowledge Graph Generation:

Deployed the Galent AI Platform within an isolated development environment to ingest the complete RVE Java/J2EE codebase and generate a contextual knowledge graph mapping:

Application components
Business workflows
Data models
Service dependencies
Integration touchpoints

This enabled rapid understanding of system complexity and modernization pathways before execution began.

Target Context Graph & Transformation Blueprint

Produced a comprehensive Target Context Graph that established source-to-target entity mappings, API transformation strategies, and UI migration analysis.

The blueprint defined modernization pathways for:

Backend APIs and services
Database schemas and entity structures
Frontend migration from legacy UI frameworks
Workflow continuity and operational parity

This approach minimized modernization risk while enabling structured execution planning.

AI Coding Agents & Spec-Driven Development

Leveraged GalentAI coding agents to accelerate development through specification-driven engineering workflows. Using OpenAPI contracts derived from the context graph, the AI-driven development process generated:

.NET 10 controllers and APIs
Angular 21 frontend components
Entity Framework Core entities
Database schemas and integration layers

Automated development significantly accelerated implementation timelines while maintaining architectural consistency and traceability.

Modern Enterprise Platform Delivery

Delivered a fully working end-to-end Angular and .NET solution with modern enterprise-grade capabilities, including:

JWT-based authentication
Immutable audit logging
Image viewer feature parity
Comprehensive automated test suite
Integration testing and Playwright automation

The new platform established a scalable and maintainable foundation for future operational growth and enterprise integration.

Solution Delivered – Execution Model

AI-led codebase discovery and knowledge graph generation using the Galent AI Platform
Target Context Graph with source-to-target transformation mapping
Spec-driven development using GalentAI coding agents
Modern Angular 21 frontend and .NET 10 backend platform
Entity Framework Core and database modernization
JWT authentication and immutable audit framework
End-to-end testing suite including xUnit, integration tests, and Playwright automation

Business Impact

The modernization initiative significantly reduced operational risk while accelerating delivery and platform readiness.

Key outcomes:

Rapid Modernization Delivery: Delivered a fully functional end-to-end proof of concept within four weeks, demonstrating the viability of AI-accelerated modernization at enterprise scale.

Elimination of Java Web Start Dependency Risk: Completely removed dependency on unsupported Java Web Start technology, eliminating a major operational and security exposure.

AI-Accelerated Engineering Execution: Enabled faster modernization through spec-driven development workflows powered by GalentAI coding agents and contextual knowledge graphs.

Improved Enterprise Readiness: Introduced modern authentication, auditability, and scalable architecture patterns aligned with enterprise integration and governance standards.

Reduced Technical Debt & Maintenance Complexity: Transitioned from tightly coupled legacy systems to a modular, maintainable architecture capable of supporting future scalability and modernization initiatives.

This engagement demonstrates how AI-powered modernization can accelerate the transformation of complex legacy enterprise systems without compromising operational continuity.

By combining AI-led discovery, contextual architecture intelligence, and spec-driven engineering, Galent helped the client rapidly modernize a mission-critical workflow platform while eliminating legacy technology risk.

Executive Insight: A Client Perspective

“Galent’s AI-led modernization approach gave us the ability to move from architectural uncertainty to a fully working modern platform in an incredibly short timeframe. Their use of knowledge graphs, context-driven transformation planning, and AI coding agents accelerated delivery while maintaining operational continuity. The engagement significantly reduced our modernization risk and established a scalable foundation for future innovation.”
– Director, Enterprise Engineering & Platform Operations.