
Legacy Systems Modernization with AI at Honda Financial Services
Executive Summary

Honda Financial Services (HSF) is the division responsible for the financial solutions of the Honda Group in Brazil, serving millions of customers with complex digital operations based on multiple legacy systems.
HSF faced the challenge of modernizing its technological base without compromising service stability. The central project was the migration of three critical legacy systems — Multimarcas, CNH, and BHB — to a new unified platform in Drupal, in the AS IS model. However, the lack of documentation and high dependency on specialists blocked the project's progress.
Squadra adopted an innovative strategy based on Artificial Intelligence, using Genius to automatically analyze, understand, and document all legacy code, unblocking the project and ensuring full autonomy for the team.
The use of AI allowed for the documentation of over 200,000 lines of code in just 1 day, reducing the project time by 60% and the total schedule by 50%, with a 30x faster unblocking than the traditional method.
The Challenge
HSF sought to modernize its technological base without compromising service stability. The central project was the migration of three critical legacy systems to a new unified platform. The technical scenario was highly challenging due to four main points:
Lack of documentation: The legacy systems (Multimarcas, CNH, and BHB) had no technical or functional documentation, making understanding the existing code extremely difficult and time-consuming.
Dependence on specialists: Knowledge of the systems was concentrated in a few Honda professionals, creating a critical bottleneck that prevented autonomous work continuity.
Integration complexity: Critical integrations, including AWS Kinesis, needed to be precisely mapped to avoid AS IS migration failures.
Legacy code volume: Over 200,000 lines of code distributed across three distinct systems, with different endpoints, business rules, and architectures that needed to be fully understood.
The Solution
Faced with the technical block caused by the lack of documentation and high dependence on specialists, Squadra adopted an innovative strategy based on Artificial Intelligence. The approach was structured in three complementary phases: Genius in action: Software archaeology with AI.
Genius in action: Intelligent PDTI with Rational Architecture
Phase 1 — Discovery: Automatic Analysis and Documentation
AI was used to perform deep analysis and automatic documentation of all legacy code from the three critical systems.
Automatic Analysis and Documentation: AI analyzed, understood, and automatically documented all legacy code, generating complete technical and functional documentation in just 1 day — work that would take months using the traditional method.
Architecture Mapping: The automatic documentation in Markdown included complete mapping of the architecture, endpoints, and business rules of the three systems.
Failure Prevention: Critical integrations, including AWS Kinesis, were precisely mapped, preventing migration failures.
Phase 2 — Knowledge Base and Virtual Specialist
With the generated documentation, Squadra structured a permanent knowledge base to ensure continuous team autonomy.
Virtual Specialist: AI acted as a
Results
The application of AI allowed regaining control of the project and eliminating operational bottlenecks, transforming a scenario of slowness into a flow of agile and predictable delivery. The automated documentation ensured greater quality and security in the system migration, reducing rework and strengthening the project's technical governance.
The result was an unblocked project, with greater team autonomy and added value for the client, who now has a permanent knowledge asset about their legacy systems. The combination of AI with human expertise unblocked the project 30 times faster than the traditional method, delivering exponential business value and positioning HSF for the next phase of its digital journey.
Metric | Result | Description |
|---|---|---|
Documentation Acceleration | 30x faster | What would take months was completed in just 1 day (200,000 lines of code documented). |
Project Unblocking | 100% unblocked | AI completely eliminated the dependence on specialists, allowing the team to resume progress. |
Time Reduction | 60% reduction | Project time was reduced from 5 to 2 months. |
Schedule Savings | 50% savings | The total schedule was reduced from 6 to 2 months. |
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