Business Rule Transformation with AI Reverse Engineering

Executive Summary

The client is an industry leading travel and vacation company that uses business rules for dynamic pricing, personalized promotions, and delivering customer-centric experiences. However, over the years, these rules have become deeply embedded in legacy systems. This situation made the rules opaque, brittle, and difficult to scale, limiting their growth. 

Overview

Businesses rely on rules to power pricing, promotions, and customer interactions. Over time, those rules can become trapped inside legacy systems (for example, COBOL, PL/SQL, or siloed databases), making them opaque, brittle, and difficult to scale.

This client needed a way to extract, analyze, and modernize thousands of deeply embedded rules to improve discoverability, scalability, and operational efficiency. Myridius partnered with them to deploy an AI-powered reverse engineering framework that transformed rigid rules into accessible business assets.

The Challenge

The client faced multiple bottlenecks caused by legacy rule management:

• Dynamic and complex rule sets: Rules were scattered across code and databases, making them hard to interpret and maintain.
• Fragmented and decentralized systems: Multiple business units managed rules differently, driving duplication and inconsistencies.
• Customer experience gaps: Opaque rules led to misaligned pricing and promotions and limited personalization.
• Business agility bottlenecks: Launching new offerings or strategy adjustments took weeks due to rigid processes.
• Operational inefficiencies: Engineers spent too much time troubleshooting and interpreting code instead of innovating.

Problem to Solution

We examined the client’s ecosystem of legacy code, documentation, and databases to understand the root causes of complexity and decentralization. From analysis and stakeholder alignment, we focused on four core goals:

• Simplify rule discoverability
• Enable business teams to query and manage rules directly
• Improve scalability without disrupting ongoing operations
• Introduce AI-powered tools for continuous optimization

We then developed a blueprint to extract, analyze, and re-engineer rules incrementally, reducing risk while maintaining business continuity.

The Solution

Myridius implemented a domain-based AI reverse engineering framework to modernize rule management into a more agile, scalable ecosystem.

What we implemented

• Code processing using LLMs: Automated parsing of COBOL, PL/SQL, and databases to surface hidden rules.
• Knowledge graphs and business rules generation: Mapped relationships between rules to improve visibility and reduce duplication.
• AI-based rules analysis and enrichment: Identified redundancies, discovered conflicts, and highlighted optimization opportunities.
• Incremental, domain-based re-engineering: Gradually migrated rules to reduce risk and ensure continuity.
• Business enablement tools: Delivered a 360° view of rules with a Business Rules Registry, Validation Workbench, and AI Query Assistant.

Results

Measurable impact on the business:

Improve Business Agility and Efficiency with Myridius

Legacy business rules often slow innovation and frustrate teams. By re-engineering rules with AI, organizations can turn hidden logic into valuable, manageable, and scalable assets that drive efficiency and growth.

With Myridius, you benefit from:

• Data and AI–first approach to transform rules into predictive, actionable insights
• Governance and adoption strategies that help transformation stick
• Domain expertise and frameworks tailored for rule-heavy industries
• Incremental, domain-based migration to a modern rules platform
• Best practices to extract and catalog rules hidden in legacy systems

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