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GenAI-Powered Legacy Modernization for Scalable Growth

Reimagining a legacy monolithic system with AI-driven microservices to enhance scalability, accelerate delivery, and ensure long-term maintainability.

Client

A leading provider of cloud-based software solutions designed to streamline the research grant lifecycle for global institutions.

Problem Statement

The client’s existing grants management application, built on Classic ASP with VBScript, had become increasingly difficult to maintain, extend, and scale. The monolithic architecture hindered agility, slowed delivery cycles, and constrained scalability, impacting the organization’s ability to innovate and meet evolving market demands.

Industry

High-Tech

Solution

Modernization

Intelligent Enterprise

genai-powered-legacy-modernization-for-scalable-growth
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Quick Summary

  • Migrated legacy ASP Classic monolith to .NET-based microservices and Vue.js microfrontends
  • Integrated Cursor AI agents to automate code generation and enforce architectural standards
  • Accelerated development velocity by 80%, significantly improving scalability and maintainability

Client Profile

A cloud software provider specializing in end-to-end research grants management for universities, funding agencies, and research organizations. The platform powers the entire grant lifecycle from submission to reporting and analytics.

Challenges: Overcoming Monolithic Limitations

  • Tightly Coupled Architecture: Existing monolith made updates complex and time-consuming.
  • Scalability Bottlenecks: Inability to scale individual modules independently.
  • Technical Debt: Legacy tech stack restricted adoption of modern tools and slowed innovation.
  • Performance Issues: Slow response times and inefficient data handling affected user experience and real-time reporting.
  • Operational Inefficiency: High maintenance overhead and long release cycles impeded growth.

QBurst Solution: AI-Accelerated Legacy Modernization

We implemented a three-phase modernization roadmap powered by Cursor AI agents, combining human expertise with AI automation to deliver a future-ready, modular architecture.

  • Foundation Architecture Setup: Established a scalable microservices framework with coding patterns, Cursor AI rules, and architectural enforcement mechanisms.
  • AI Integration:
    • Defined reusable rules and patterns for CQRS, controllers, and frontend components
    • Built automated compliance and migration guides for quality and consistency
    • Integrated Figma MCP for extracting UI components directly from designs
  • AI-Driven Development Workflow:
    • Automated migration of ASP pages to .NET microservices and Vue components
    • Context-aware code generation using “one-shot” prompts to create APIs, components, tests, and documentation

Implementation Approach: Modular, Automated, Future-Ready

  • Strangler-Fig Migration Pattern: Ensured risk-free, incremental modernization while maintaining business continuity.
  • AI-Guided Code Generation: Reduced manual development effort through automated, pattern-consistent code creation.
  • Microservices Architecture: Enabled independent service deployment and fault isolation for better scalability.
  • Standardized Patterns and Prompts: Ensured code consistency and maintainability across services.
  • Developer Onboarding Efficiency: AI-driven documentation and contextual automation accelerated onboarding for new developers.

Impact

  • Accelerated Development: 80% faster development velocity with AI-assisted code generation and architectural enforcement.
  • Independent Domain Scalability: Enabled independent scaling of business domains such as Auth, Committees, and Applications.
  • Lower Operational Costs: Reduced operational costs through modular design and automation-led efficiency.
  • Improved Maintainability: Improved maintainability and developer productivity with enforced coding standards.
  • Enhanced Performance: Improved performance and user experience through modern, loosely coupled architecture.

Client Profile

Challenges

QBurst Solution

Implementation

Impact