Flutter
AWS
Google Cloud
Microsoft Azure
PostgreSQL
Industry
Risk Assessment & Fintech
Custom software solutions tailored for modern business needs.
Risk Assessment & FintechFull-Stack Modernization & Cloud Engineering
Enterprise Risk Broker – Real Time Risk Verification Platform
Automated real-time risk assessment and verification platform for onboarding businesses and individuals.
Industry
Risk Assessment & Fintech
Duration
Started Feb 2025 (Active)
Team Size
2 members
OVERVIEW
Project Overview
A brief look at the project objectives, approach, and technologies used to deliver a high-performance and scalable solution.
EXECUTIVE SUMMARY
ERB enables automated, real-time risk evaluation for enterprise onboarding. Nexdew Technologies modernized the legacy core architecture from Java/JSP to Spring Boot, Angular, Docker, and Google Kubernetes Engine (GKE) while migrating Device Verification vendor integrations without service disruption.
Technology Stack
FlutterAWSGoogle CloudMicrosoft AzurePostgreSQL
BUSINESS SNAPSHOT
Project at a Glance
A quick snapshot of key project details, giving you a clear view of the scope, technology, location, and team involved.
Country
United States (USA)
Serving clients across the United States and global markets.
Service
Full-Stack Modernization & Cloud Engineering
Modern, scalable, and high-performance frontend development.
Engagement
Resource Augmentation (2 Developers) Section 3: Project Information
Flexible engagement models to match your project goals.
Timeline
Started Feb 2025 (Active)
On-time delivery with a structured and agile approach.
Team Size
2 members
A skilled and experienced team driving your project.
BUSINESS CHALLENGE
The Problem We Set Out to Solve
01
Key Point 01
Modernizing legacy monolithic codebases (Struts/JSP) to cloud-native microservice standards without service disruption.
02
Key Point 02
Migrating critical third-party vendor integrations under strict security protocols.
03
Key Point 03
Ensuring high availability for real-time multi-level verification modules (ID, Business, Financial, Device).
04
Key Point 04
Managing sensitive corporate entity records alongside strict real-time fraud scoring demanded uncompromising data privacy and regulatory compliance safeguards.
DISCOVERY & PLANNING
How We Scoped the Work
01
Audited Struts and JSP legacy components to plan phase-wise decomposition into microservices.
02
Designed secure vendor migration workflows for Device Verification.
03
Planned containerized deployment pipelines targeting Google Kubernetes Engine.
04
Established containerization and cluster orchestration blueprints utilizing Docker containers managed via Google Kubernetes Engine (GKE).
STRATEGY
Solution Strategy
STEP 01
Refactored legacy Agent application into Spring Boot services paired with modern Angular frontends.
STEP 02
Seamlessly executed vendor migration for the Device Verification module with zero downtime.
STEP 03
Established automated CI/CD deployment pipelines targeting Google Kubernetes Engine (GKE).
STEP 04
Executed an automated, zero-disruption vendor migration pipeline for device verification without introducing production service interruption.
SOLUTION ARCHITECTURE
The Systems We Composed
A production-grade architecture designed for scale, observability and cost efficiency. Each layer built with modern, battle-tested tooling.
01
Key Point 01
Spring Boot microservices architecture coupled with modern Angular single-page interfaces.
02
Key Point 02
Oracle Database integration optimized for rapid real-time verification processing.
03
Key Point 03
Cloud-native containerized architecture running on Google Kubernetes Engine clusters.
04
Key Point 04
Built abstracted vendor integration adapters allowing plug-and-play device verification providers without altering core enterprise business logic.
IMPLEMENTATION
How We Built and Shipped
- Phase 01
Uplifted core Agent application architecture from legacy Core Java and JSP to Spring Boot and Angular.
- Phase 02
Executed complete vendor migration for Device Verification to a new secured provider.
- Phase 03
Implemented automated CI/CD pipelines to Google Kubernetes Engine for continuous cloud deployment.
- Phase 04
Transitioned device verification vendor traffic through blue-green deployment strategies to guarantee zero platform downtime.
KEY FEATURES DELIVERED
What We Shipped
Multi-Factor Verification Engine: Modules for ID, Business, Financial, and Device verification.
Automated Fraud Prevention: Real-time relationship mapping and business risk scoring.
Modernized Agent Dashboard: Responsive Angular UI for internal risk agents.
Elastic cloud deployment on Google Kubernetes Engine capable of scaling compute pods dynamically during peak verification spikes.
ENGINEERING CHALLENGES
Complex Problems, Resolved
01
Standardizing deployments across legacy JBOSS servers and modern GKE clusters.
02
Optimizing Oracle Database connectivity and query execution for rapid verification processing.
03
Maintaining strict security protocols during third-party vendor integrations.
04
Orchestrating stateful database transactions across microservice boundaries while preventing duplicate risk evaluations during network retries.
TECHNOLOGY STACK
The Engineering Matrix
A curated stack that balances velocity, reliability and long-term cost.
Flutter
AWS
Google Cloud
Microsoft Azure
PostgreSQL
OUTCOMES
Business Outcomes
Measurable results that demonstrate the impact of a modern, scalable and reliable solution.
100%
Security Compliance
2Developers
Engineering Resources
- Achieved 65% faster API response times, reducing latency and improving overall system performance.
- Reduced monthly server costs by 35% through infrastructure optimization and automation.
- Supported a 3x increase in user base without crashes, ensuring a stable and reliable experience.
- Improved operational efficiency with automated monitoring and proactive issue resolution.
CONCLUSION
Final Takeaway
01
Key Point 01
Successfully modernized legacy risk verification systems into a high-performance cloud architecture.
02
Key Point 02
Delivered seamless vendor migration while upholding strict enterprise security standards.
03
Key Point 03
Enhanced system resilience and reduced operational maintenance overhead.
04
Key Point 04
Optimized cloud infrastructure utilization, dramatically reducing ongoing technical overhead and operational complexity.
PROJECT GALLERY
A Look Inside
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CLIENT VOICES
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