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Gadgeon is a global engineering and technology services provider with over 15 years of experience supporting enterprises in building and modernizing complex digital platforms. Our teams bring hands-on experience across data platforms, integration architectures, enterprise applications, and AI enablement.
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In Banking, Financial Services and Insurance, AI initiatives increasingly depend on the strength of underlying data, integration, and platform foundations. Our BFSI practice focuses on helping banks and lenders modernize these foundations so AI efforts can move beyond pilots and deliver measurable business impact.

Understand Where You Stand on AI Readiness

A quick assessment to help banking leaders evaluate AI readiness and define a clear, actionable roadmap aligned to business priorities.

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AI Readiness

Why AI Success Starts with Architecture

A concise POV on why data foundations, integration patterns, and operating models determine whether AI initiatives scale or stall in banks.

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AI Readiness

Client Stories

Discover how Gadgeon's tailored engineering solutions have transformed businesses, solved complex challenges, and driven innovation across industries.

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Gadgeon is an extended engineering center for us, and they provide developers, testers, and network engineers to enhance our capabilities.

tushar
Tushar Sachudev
CTO, KORE

At the outset of our project, Gadgeon did an excellent job of understanding and documenting our requirements and use cases.

tushar
Tom Penne
Engineering Team Leader, Pella

In their long-term partnership, the team has cultivated a strong rapport and rate of success with their partner by taking time to clearly understand their highly-regulated industry.

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Craig Carder
Pres. & Engineering Principal, C3

I want to thank Gadgeon team for understanding our requirements and on-time delivery with excellent quality, which exceeded our expectations.

Bruce Crenshaw
Bruce Crenshaw
Director of Hardware & IT, Odermark

Gadgeon team is comprised of competent and curious coders who are eager to understand the technology they're working with.

Surendar Magar
Surendar Magar
CEO, LifeSignals
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Case Studies

Creating an AI-Ready Data Foundation for a U.S. Mortgage Lender

A U.S.-based mortgage lending firm operating multiple SaaS platforms across its lending, HR, and operational environments.

Streamlining Enterprise IT Operations with ServiceNow Automation

A U.S.-based enterprise operating multiple digital platforms faced growing complexity in managing IT services across teams and systems.

Turning Customer Feedback into Strategic Insight with AI

A U.S.-based enterprise sought better visibility into how customers perceived newly launched products and wanted a structured way to analyze feedback across digital platforms.

Consolidating Legacy Data into a Centralized Analytics Platform

The customer was interested in developing a Gateway that not only interfaces with EV charging stations, but also other Building management

Modernizing Legacy Applications Through Cloud Migration

A global enterprise operating multiple legacy applications sought to modernize its technology environment by migrating critical systems to the cloud.

Automating Compliance Processing With Robotic Process Automation

An enterprise organization sought to streamline a recurring compliance-related payroll process that required monthly submission of employee contribution data to a regulatory portal.

Improving Customer Support Efficiency with an AI-Powered Service Desk Assistant

A cloud service provider wanted to improve customer support responsiveness while enabling its service desk team to focus on more complex issues.

Client Profile

A U.S.-based mortgage lending firm operating multiple SaaS platforms across its lending, HR, and operational environments.

The Challenge

The institution relied on 12+ SaaS platforms across different clouds and technology stacks, including:

Journey (ATS), Paycom (HR/Payroll), Encompass (LOS), Azure AD (Identity), Office 365, RingCentral, Compensafe, LastPass, SimpleNexus, accounting applications, and internal production and operations systems.

This environment created several challenges:

  • No shared data model across systems
  • Employee changes required manual updates in multiple platforms
  • Operational data remained fragmented across applications
  • Limited audit visibility and governance
The Approach

Gadgeon designed a three-layer architecture centered around:

  • Event-driven integration to synchronize activity across systems
  • Enterprise workflow automation for provisioning and compliance processes
  • Master data management to establish a consistent enterprise data model
Key Outcomes
  • Automated employee onboarding and de-provisioning across 12+ systems
  • Near real-time synchronization of operational data
  • Automated data scrubbing across platforms to support CCPA compliance
  • Personalized workflows triggered by real-time business events
  • Consistent enterprise data foundation enabling AI initiatives
Strategic Impact

A single message bus transformed how the institution's systems worked together, creating a unified data foundation that enabled scalable automation and future AI capabilities.

Client Context

A U.S.-based enterprise operating multiple digital platforms faced growing complexity in managing IT services across teams and systems.

The Challenge

The organization relied on legacy tools such as Zendesk and other fragmented platforms to manage IT services and operations. This environment created several operational issues:

  • Slow incident response and longer service resolution times
  • Manual processes for incident, change, and asset management
  • Limited coordination across teams during system changes
  • Lack of centralized visibility into service performance and compliance

Leadership wanted to modernize IT service management and establish a more structured operational environment.

The Approach

Gadgeon implemented ServiceNow IT Service Management (ITSM) to centralize incident, change, and service workflows.
The solution included:

  • Automated incident logging and routing through a self-service portal
  • Structured change management with CAB approvals and audit validation
  • Workflow automation for routine tasks such as user provisioning and access management
  • Integration between Salesforce and ServiceNow to synchronize customer and account data
Key Outcomes
  • Faster incident response and improved service resolution
  • Greater operational visibility through real-time dashboards
  • Stronger governance through structured change approvals
  • Improved compliance and reduced operational risk
Strategic Impact

By modernizing its IT service management environment, the organization improved operational efficiency, reduced service disruptions, and established a scalable foundation for future digital and automation initiatives.

Client Context

A U.S.-based enterprise sought better visibility into how customers perceived newly launched products and wanted a structured way to analyze feedback across digital platforms.

The Challenge

Customer feedback was scattered across multiple channels including e-commerce platforms, public forums, and online reviews. While valuable insights existed in this feedback, the organization lacked an effective way to consolidate and analyze it at scale.

Without a centralized analysis capability, identifying product strengths, weaknesses, and emerging customer concerns was difficult.

Leadership wanted a solution that could transform unstructured feedback into actionable insights to guide product improvement and strategic decision-making.

The Approach

Gadgeon developed an AI-powered sentiment analysis platform that automatically collected customer reviews from multiple sources and analyzed them using advanced language models.

The system categorized feedback, identified sentiment patterns, and generated structured insights through interactive dashboards.

The platform allowed product teams to explore feedback by category, product attributes, and sentiment trends.

Key Outcomes
  • Consolidated feedback from multiple public platforms into a single insight engine
  • Automated sentiment analysis across large volumes of customer reviews
  • Identified most appreciated product features and least-liked attributes
  • Enabled leadership teams to make data-driven product decisions
Strategic Impact

By transforming unstructured customer feedback into actionable insights, the organization gained a clearer understanding of customer sentiment and improved its ability to refine products based on real-world feedback.

Client Context

A global enterprise operating multiple legacy systems across regions sought to modernize its data environment as part of a broader business intelligence convergence initiative.

The Challenge

Operational data was distributed across multiple legacy platforms and databases, including systems supporting ERP, accounting, and workflow applications.

Because these systems evolved independently, data structures varied significantly and information was difficult to consolidate for enterprise analytics.

The organization wanted to migrate data from multiple systems into a centralized cloud platform while ensuring scalability and continuous synchronization across regions.

The Approach

Gadgeon designed a microservices-based architecture to move data from distributed systems into a centralized Azure data environment.
The solution included:

  • Producer microservices to extract data from legacy systems
  • Event streaming using Kafka for reliable data movement
  • Data transformation into a standardized JSON format
  • Continuous ingestion of historical and real-time data into the centralized platform
Key Outcomes
  • Consolidated data from multiple legacy systems into a unified cloud environment
  • Enabled near real-time data synchronization across global systems
  • Created a standardized data format for enterprise analytics
  • Supported scalable data processing across multiple regions
Strategic Impact

By consolidating fragmented data into a centralized platform, the organization established a reliable foundation for enterprise analytics and future AI-driven insights.

Client Context

A global enterprise operating multiple legacy applications sought to modernize its technology environment by migrating critical systems to the cloud.

The Challenge

Several business-critical applications had been running on legacy infrastructure for more than a decade. Documentation was limited, and internal teams were focused on new development initiatives.

Migrating these systems to a modern cloud environment required deep understanding of legacy components while ensuring that ongoing operations and development efforts were not disrupted.

The Approach

Gadgeon partnered with the organization to migrate legacy systems and supporting components to Azure cloud.
The migration included:

  • Containerizing legacy applications and deploying them on Azure Kubernetes Service (AKS)
  • Modernizing selected components using embedded application servers
  • Migrating databases to managed cloud environments
  • Implementing CI/CD pipelines and monitoring tools for improved operational visibility

Performance optimization and scalability testing were completed before the platform was handed over to the client's engineering team.

Key Outcomes
  • Successful migration of legacy applications to the Azure cloud
  • Improved scalability and operational monitoring
  • Reduced reliance on aging infrastructure
  • Enabled internal teams to focus on new product development
Strategic Impact

By modernizing its legacy application environment, the organization created a scalable cloud platform that supports continued digital innovation and operational efficiency.

Client Context

An enterprise organization sought to streamline a recurring compliance-related payroll process that required monthly submission of employee contribution data to a regulatory portal.

The Challenge

Each month, the finance team was required to generate contribution reports for employees across multiple locations. The process relied on manually compiling employee data, creating structured files, and uploading them to a regulatory portal.

This repetitive activity required significant manual effort and introduced risks related to data accuracy and processing delays.

Leadership wanted to automate the process while ensuring that employee data was sourced directly from the HR platform.

The Approach

Gadgeon implemented a robotic process automation (RPA) solution using UiPath to automate the entire workflow.
The automation solution:

  • Retrieved employee data directly from the HR system via APIs
  • Generated contribution files in the required format
  • Validated the data against portal requirements
  • Uploaded the files and generated the required payment challan
  • Sent automated notifications to HR and finance teams
Key Outcomes
  • Reduced manual effort by approximately 90%
  • Reduced processing time from nearly 12 hours to about 20 minutes
  • Improved accuracy by eliminating manual data handling
  • Strengthened compliance through automated validation
Strategic Impact

By automating a repetitive compliance process, the organization improved operational efficiency and enabled finance teams to focus on higher-value activities.

Client Context

A cloud service provider wanted to improve customer support responsiveness while enabling its service desk team to focus on more complex issues.

The Challenge

Customer service teams were handling a high volume of routine support requests, many of which involved frequently asked questions. This created delays in addressing more complex technical issues and limited the team’s ability to scale support services efficiently.

The organization wanted a digital assistant that could handle routine inquiries, operate continuously, and integrate with existing service desk workflows.

The Approach

Gadgeon designed and implemented an intelligent service desk assistant using the Microsoft Bot Framework.
The solution included:

  • A chatbot trained on a structured knowledge base of common support questions
  • Multi-channel access through web applications and collaboration platforms
  • Automated routing to human agents for complex issues
  • Queue management and multilingual support for broader customer accessibility
Key Outcomes
  • Automated handling of frequently asked customer inquiries
  • Increased self-service capability for end users
  • Reduced workload for service desk agents
  • Improved customer satisfaction and response times
Strategic Impact

By introducing an intelligent service assistant, the organization improved support efficiency while allowing service teams to focus on complex, high-value customer interactions.

Our commitment
to quality

Gadgeon is committed to deliver excellence in solution design and development services. Our quality policy states:

On time delivery of Innovative solutions and services within budget and agility by meeting all customer and regulatory requirements.

Empowering employees to deliver quality solutions and services with passion

Continuous improvement in solution development and processes

Meet Our Experts

Connect with our experts to discuss how AI readiness and technology foundations apply to your organization.

Wes Schropp LinkedIn

Wes Schropp

Regional Director - Gadgeon Systems

LinkedIn

Jay Shankar

Principal Consultant - Gadgeon Systems

Let's connect today and move your enterprise confidently forward.

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