Case Study

Major Enterprise Optimizes Operations with Intelligent Data Migration

Executive Summary

In a competitive enterprise environment, our client aimed to modernize legacy systems and unlock the value of distributed data. Viarog designed and implemented an AI-powered data migration strategy to accelerate digital transformation, reduce operational complexity, and support real-time analytics.

Industry: Enterprise / Data-Intensive Operations
Focus Areas: AI, Cloud Migration, Data Intelligence, Scalable Infrastructure
Solution: AI-driven Data Platform & Cloud Services

Reviewed on
5 / 5 üzerinden değerlendirildi
30,000
+

Hours delivered back to the business

100
+

SOX compliance in Settlement process automation

95
+

Success rate of bot case completion

6
+

For functional release of OBT, RTS and OGS

The Challenge

The enterprise faced the following challenges:Fragmented data systems across business units, hindering analytics and decision-making.

Legacy infrastructure inefficiencies, increasing operational costs.Limited ability to leverage data for strategic forecasting and predictive insights.Demand for a secure, scalable architecture aligned with sustainability goals.

They required a solution that would modernize their data estate, improve performance, and provide future-proof analytics.

What did
Viarog do

Viarog’s ability to combine advanced technology, security, and scalability with agility made us a trusted technology partner for this project. By aligning artificial intelligence, cloud infrastructure, and cybersecurity practices, Viarog delivered a solution designed to support operational efficiency, regulatory compliance, and long-term digital growth. The project was executed across two key workstreams: AI-Driven Automation and Intelligent Application Development, supporting the client’s transition toward a more resilient and data-driven digital architecture.

AI-Driven Automation

Viarog designed and implemented intelligent automation workflows to streamline critical business processes. Using AI-supported decision engines and secure cloud infrastructure, we identified, developed, tested, and deployed automation scenarios that reduced manual operations and increased processing efficiency. These solutions were implemented across multiple functional areas, enabling faster response times, improved accuracy, and measurable operational savings.

The Results

The Technologies We Used to Sup

JavaScript
TypeScript
Node.JS
React
Swift
Java
Objective-C
RxJava

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