How we reduced technical debt for a Fintech scale-up using AI agents
Deployed AI-augmented engineering squads to systematically identify, refactor, and document legacy code, reducing technical debt by 40% in just 3 months while maintaining feature velocity.
40% reduction in technical debt metrics
Test coverage increased from 35% to 85%
Feature delivery velocity restored to pre-scale levels
Onboarding time for new devs reduced by 2 weeks
The Challenge
Understanding the problem before designing the solution.
The client, a rapidly growing fintech scale-up, was bogged down by accumulating technical debt. Feature delivery had slowed by 50% due to fragile legacy code, lack of documentation, and brittle test coverage. They needed a way to pay down debt without pausing product development.
Our Solution
A senior-led, evidence-first approach to the problem.
RSVR deployed an AI-augmented squad specialized in modernization. We used proprietary AI agents to map the codebase, generate missing unit tests, and propose safe refactoring paths. Our senior engineers reviewed and merged these changes, ensuring safety and compliance throughout the process.
Key Deliverables
AI-driven static analysis and refactoring
Automated unit test generation
Legacy code documentation
CI/CD pipeline optimization
Zero downtime during refactoring
Knowledge transfer to internal team
The outcomes we delivered.
Measurable results achieved through senior-led, evidence-first delivery.
40% reduction in technical debt metrics
Test coverage increased from 35% to 85%
Feature delivery velocity restored to pre-scale levels
Onboarding time for new devs reduced by 2 weeks
Technologies used
The stack we selected and delivered on.
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