Assessing a 4GL Legacy Architecture for a Leading Insurer in 12 Weeks
Client Overview
The client is one of the largest insurance enterprises in North America, with 150+ applications supporting the operations that keep its insurance business running. Its technology estate spans the insurance lifecycle, from policy administration and underwriting through claims, billing, payments, agency management, and compliance. The company was preparing to bring this extensive application landscape together under a modern Insurance Management System (IMS), with a need to establish a clear picture of its existing systems and how they fit into the future architecture.
Replacing Manual Reverse Engineering with Evidence-Driven Discovery
A manual assessment of the legacy estate would have taken 12–18 months, delaying modernization before it could start. The objective was to replace it with a faster, evidence-driven way to understand the system landscape.
01
Undocumented System Behavior
Decades of business logic lived inside the code itself, with limited documentation to explain what the systems did.
02
Tribal Knowledge Dependency
Understanding of the platform sat with a shrinking pool of subject matter experts, creating risk for any transformation effort.
03
Batch Dependencies
The batch-processing ecosystem ran as an operational black box, with unclear scheduling patterns and dependencies across applications, scripts, databases, and external services.
04
Business Logic Embedded in Code
Core business rules sat deep within the legacy code, making system behavior harder for new engineering teams to interpret.
Decoding 1M+ Lines of Legacy Code with Legacy Lifter
A structured, evidence-driven process turned decades of undocumented complexity into a clear, evidence-backed blueprint.
01
Structural and Semantic Discovery
Parsed and analyzed over 1 million lines of proprietary 4GL code across 1,000+ files to understand system structure, business logic, execution flows, and dependencies. Produced 411 implementation-ready user stories and the organization’s first comprehensive system manual for the platform.
02
Batch & Scheduler Intelligence
Analyzed the batch ecosystem to understand job behavior, scheduling patterns, execution relationships, and dependencies across applications, scripts, databases, and external services.
03
Application Portfolio & API Inventory
Built a structured view of the application estate by identifying technology stacks, architectural patterns, application dependencies, APIs, and integration points.
04
Business Capability Mapping
Connected applications to the business capabilities they support through a structured model covering domains, capabilities, and system features.
05
Deep Core System Analysis
Traced entry points across user interfaces and batch processes while identifying shared logic and tightly coupled components. Highlighted areas suited for faster modernization alongside components requiring careful refactoring.
The Payoff: A Legacy Estate the Business Finally Understands
Discovery Timeline Cut by Months
Legacy Lifter analyzed 1M+ lines of code, 8,900+ batch jobs, and 150+ applications in 12 weeks, replacing a discovery effort that could have taken up to 18 months.
Business Logic Became Accessible
The analysis extracted 6,000+ business rules from source code and mapped them to execution flows, creating documented knowledge that teams could use beyond individual SME expertise.
The Estate Became Measurable
The assessment surfaced 499 .NET projects, 3,174 endpoints, and 20+ enterprise domains, giving leadership a clearer view of the technology footprint and its alignment with business capabilities.
A Defined Path to the Future-State IMS
The engagement produced a future-state IMS architecture and roadmap grounded in evidence rather than assumption.
You Can't Modernize What You Don't Understand
Modernization decisions become difficult when the systems supporting the business remain a black box. Building a clear understanding of how applications, business logic, and dependencies work together creates the foundation for making meaningful change. For organizations carrying decades of legacy complexity, that understanding turns modernization from a high-stakes exercise into a path they can approach with confidence.
Claims dispatch activities moved through an automated workflow and reduced dependency on manual coordination and repetitive operational follow-ups.