App Modernization using Generative AI in Weeks for Fintech

Key Highlights

  • The project addressed the complexity of transitioning from a legacy system to microservices, aiming to resolve system-wide disruptions, scalability limitations, and innovation constraints.
  • Transitioning to microservices posed risks such as service disruptions, compatibility issues, and lengthy deployment times, impacting customer satisfaction and operational continuity.
  • Automated monolithic code analysis defined precise fintech-specific service boundaries, and optimized secure microservices with minimal manual effort, ensuring compliance & modularity.
  • The transition improved fintech scalability, efficiency, and compliance while reducing costs and speeding up time-to-market, ensuring uninterrupted service and enhancing competitiveness.

Problem Statement

01

Complex Monolithic Architecture: The monolithic architecture caused system-wide disruptions, leading to delays, expensive deployments with limited scalability and innovation.

02

Challenges in Transitioning: Transitioning to microservices poses risks like service disruptions, compatibility issues, and time consumption, impacting customer satisfaction and continuity.

03

Uncertain ROI: Uncertain ROI makes it hard to secure funding for modernization, while the legacy system's rigidity stifles innovation and market adaptability, hindering growth.

Solution Overview

01

Microservice architecture is built by automating monolithic code analysis, identifying service boundaries, and generating optimized microservices blueprints in Java.

02

Automated code refactoring tasks, transforming the monolithic codebase into modular, independent microservices with minimal manual intervention, leveraging advanced algorithms.

03

Ensured code quality and comprehensive documentation throughout the transformation process by automatically generating unit tests, API documentation, and architectural diagrams.

04

Gen AI optimized deployment through automated containerization, orchestration, and CI/CD pipelines, ensuring smooth and efficient microservice deployment.

05

Gen AI aids smart go-live management with tools for phased deployment, automated rollbacks, and real-time monitoring, minimizing service disruption risks during the transition.

Business Impact

01

Time and Cost Efficiency: Gen AI’s automation reduced time and development costs, enabling rapid market adaptation, lower expenses, and increased profitability.
0
% cut
Development Time & Costs

02

Scalability and ROI: Transitioning to microservices improved scalability and boosted return on investment through efficient resource scaling and cost savings.
0
%
Increased ROI

03

Risk Mitigation: Gen AI automated quality assurance, documentation, and deployment, reducing risks, ensuring smooth transitions, and minimizing disruptions.
0
%
Reduced Risk of Errors

ABOUT THE

Project

The project achieved significant growth and innovation through a legacy modernization project powered by our iBEAM, an AI-driven solution that automated the complex process of transitioning from a monolithic architecture to microservices, reducing development time and costs. Gen AI’s automation guarantees high-quality code, comprehensive documentation, and smooth deployment, minimizing risks and disruptions. The microservices architecture improved scalability and ROI, allowing the company to adapt to market demands more rapidly and achieve greater profitability.

Tech Stack

Testimonials of Our Happy Clients

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