New, end-to-end application for managing insurance producers’ banking and compensation details ensures accuracy and efficiency.
Client
A leading mutual life insurance provider
Goal
Rebuild the legacy system platform into a scalable, user-friendly platform with advanced functionality for business teams
Tools and Technologies
React Js, Node Js, PostgreSQL, Bitbucket, Jenkins
Business Challenge
The organization faced a critical need to modernize its legacy mainframe system, used to maintain the banking details of brokers and producers for compensation-related purposes. Zeus lacked flexibility, scalability, and the ability to deliver modern user experience. Business stakeholders sought a system rebuild using a modern tech stack to address the limitations of the existing platform and improve usability and functionality for key teams. The goal was to create a system that could scale with the organization’s needs, streamline operations, and provide an intuitive experience for users.
Solution
- Built the new application from scratch with scalable backend services and intuitive frontend UI
- Designed a modern interface using React JS for the Data Capture System (DCS) to manage producer and bank details efficiently
- Developed robust backend services using Node.js for performance and scalability
- Enabled secure and seamless API integration through Apigee
- Leveraged PostgreSQL for reliable and flexible database management
Outcomes
- Scalable and reliable system supporting future growth and consistent performance
- Responsive and intuitive UI delivering enhanced user experience compared to the legacy system
- Advanced functionality allowing users to easily add, edit, filter, and search broker and bank details
- Faster development cycles achieved through modern frameworks and tools, accelerating deployment timelines
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Strengthening Product Data Management
Delivered a secure, scalable, and user-friendly platform that transformed product data management, improved efficiency, and ensured governance.
Client
The large NY-based insurance and investment company
Goal
Build a secure, scalable, and governed platform for product data management while eliminating legacy inefficiencies
Tools and Technologies
Java 21, Spring Boot, AWS, Jenkins, Stone Branch, Jira, Microservices, Redshift, Aurora, DynamoDB, Angular, JS, MYSQL, EKS, SQSBusiness Challenge
The client needed a modern and secure interface for managing entity data such as mutual funds and ETFs. Legacy dependencies and the absence of a centralized UI led to inefficiency, limited user control, and slower operations. The challenge was to design a governed, user-friendly, and scalable solution that could improve efficiency and security without disrupting downstream systems.
Solution
- Built a decentralized entity management platform with a secure UI for entity data and bulk file uploads with built-in validations
- Designed microservices with a staging database for faster, modular delivery
- Implemented LDAP-based authentication and role-based access for enhanced governance and security
- Deployed on containerized EKS with multi-region scalability to ensure resilience and high performance
Outcomes
- Accelerated delivery with microservices, CI/CD, and file-based updates reducing manual effort
- Empowered users with a role-based UI and approval workflows for direct entity data management
- Strengthened architecture with containerized EKS deployment and LDAP-based authentication for scalability, security, and resilience
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Modernizing Product Data for Future Growth
A leading enterprise partnered with Iris to modernize its product data infrastructure, delivering a secure, scalable platform that streamlined access, ensured governance, and preserved continuity for critical services.
Client
A large NY-based life insurance and investment company
Goal
Unify product data access with secure APIs, modern architecture, and seamless integration while minimizing disruption
Tools and Technologies
Java 21, Spring Boot, AWS, Jenkins, Stone Branch, Jira, Microservices, Redshift, Aurora, DynamoDBBusiness Challenge
A leading enterprise needed to modernize its product data infrastructure to meet evolving business and digital transformation needs. The existing data mart lacked a secure, standardized way to share information with downstream services, creating governance and consistency challenges. Meanwhile, a legacy system supported critical microservices, and moving to a new platform risked disrupting integrated data flows. The organization required a secure, scalable solution for future growth with continuity.
Solution
- Built Product Data Services, a Spring Boot and Java 21 microservices platform on AWS with Redshift and Aurora, enabling secure, flexible API access using tagged identifiers
- Deployed Product Data Submitter, a DynamoDB-powered service that populated data via Stone Branch workflows, ensuring existing microservices continued to function without change
- Designed a scalable architecture requiring minimal code changes for future expansion
Outcomes
- Centralized access to product and entity data with secure, tag-based APIs and a governed UI
- Seamless modernization of backend systems without disrupting existing microservices
- Accelerated delivery through microservices, CI/CD, and automated file-based updates
- Reduced manual effort and improved developer productivity with streamlined workflows
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AWS-Based Financial News Feed Portal
Custom integrate AWS-hosted portal with secure API integration, SSO, and a user-friendly interface to deliver timely financial news.
Client
Large NY-based life insurance and investment company
Goal
Develop a secure AWS-based portal to deliver financial news with API integration, SSO, and consistent user experience
Tools and Technologies
NET 8.0, ASP.NET MVC, AWS, EC2, Lambda, S3, SES, API GatewayBusiness Challenge
The client needed a custom, AWS-hosted application to deliver financial news via external API integration. The solution had to support secure access for both internal and external users with Ping-based SSO. Additionally, the interface required UI/UX alignment with an existing legacy platform for consistency. Timely news delivery also was critical, compelling automated data refreshing every 15 minutes to ensure accuracy and relevance.
Solution
- Automated data ingestion using AWS Lambda to fetch and process news from external API every 15 minutes
- Developed an ASP.NET MVC application on Amazon EC2 with a user-friendly dashboard, filtering, and search capabilities
- Integrated Ping Identity for secure, role-based SSO access for internal and external users
- Secured communication with external API through IBM DataPower and mutual TLS
- Designed UI/UX to mirror the legacy platform for a seamless and familiar experience
Outcomes
- Reduced licensing costs by replacing full third-party access with targeted API usage
- Gained full application ownership and flexibility for future enhancement and customization
- Strengthened security with mutual TLS and DataPower integration
- Simplified authentication and authorization through SSO integration
- Improved operational flexibility with configurable refresh intervals and archiving strategies
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Streamlining Document Workflow Efficiency
Iris modernized a document workflow system with advanced search, intuitive UI, and seamless integration for higher productivity.
Client
A leading mutual life insurance provider
Goal
Build a robust, user-friendly portal to streamline document review workflows with seamless integration and advanced search
Tools and Technologies
React, Node.js, optimized APIs, suggestive search, advanced filtering, seamless system integrationBusiness Challenge
The organization needed a robust solution to manage document workflows requiring editing or review before publishing, storing, or delivering to customers. Existing processes were slow and inefficient, making it difficult for teams to manage documents seamlessly. The key goals were to streamline review and editing, ensure smooth integration with enterprise systems, and create a user-centric portal that improved search, filtering, and overall workflow efficiency.
Solution
- Upgraded front-end features to improve usability and performance
- Designed an advanced filtering interface for more precise document search
- Developed reassignment functionality with intelligent, suggestive search capabilities
- Enhanced case manager search to enable faster and more accurate results
- Optimized API integration for smooth communication between frontend and backend systems
Outcomes
- Greater filter accuracy enabling precise document and case manager search
- Modern, intuitive interface boosting user satisfaction and productivity
- Seamless performance of search and reassignment features without slowing the system
- Streamlined workflows resulting in faster and more reliable document management
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Scaling Absence Management with Modern APIs
Delivering a comprehensive absence management solution by integrating APIs, upgrading data formats, and ensuring scalability across clients.
Client
A leading mutual life insurance provider
Goal
Enhance absence management capabilities by integrating a SaaS platform, upgrading data exchange, and enabling scalable client support
Tools and Technologies
Angular, .NET Core, SQL ServerBusiness Challenge
An enterprise needed to strengthen its absence management program by leveraging a third-party SaaS platform to support multiple leave plans including FMLA, ADA, STD, LTD, and state-mandated leaves. Key challenges included integrating internal insurance APIs with the SaaS platform, upgrading LIMRA data-exchange format from version 1.0 to 2.0 for interoperability, and ensuring a client-centric framework that could scale across multiple clients and vendor partners while maintaining accuracy and reliability.
Solution
- Developed new APIs to integrate internal systems with the SaaS platform, aligned with LIMRA 2.0
- Implemented Spring Boot to build scalable, maintainable services
- Deployed APIGEE for secure API management and efficient integration
- Adopted Splunk for real-time monitoring, observability, and faster issue resolution
Outcomes
- Delivered comprehensive absence management solutions across external clients and partners
- Enhanced accuracy and interoperability with LIMRA 2.0 upgrade
- Built a modular API framework to scale for future enhancements and onboarding
- Strengthened system performance and availability through Splunk monitoring
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Modern Deal & Issuer Management System
Iris replaced a legacy SharePoint solution with a modern, scalable system that improved deal and issuer data management, efficiency, and insights.
Client
The large NY-based insurance and investment company
Goal
Develop a modern, scalable system to manage deal and issuer data efficiently while eliminating legacy costs and inefficiencies
Tools and Technologies
.Net Core 6(API) , Background Service, Angular 14, SQL ServerBusiness Challenge
The client’s SharePoint-based system for managing deal and issuer details faced major limitations. As data volume and user count increased, the platform became slow, difficult to customize, and expensive to maintain. Integration with other critical tools was limited, reducing efficiency and scalability. These constraints created risks to effective deal management and hindered the ability to scale operations.
Solution
- Built a modern web-based system using Angular (front-end), .NET Core (back-end), and SQL Server (data storage)
- Developed a self-service portal for internal teams to easily manage deal and issuer data
- Automated data ingestion, cleaning, and storage with a background service for accuracy and consistency
- Integrated Splunk and Application Insights to enable real-time monitoring of system health and performance
Outcomes
- Substantial cost savings by eliminating SharePoint licensing and maintenance expenses
- Improved performance and scalability with faster system response and ability to support more users
- Enhanced user experience through a modern, intuitive, and efficient interface
- Increased automation, reducing manual tasks and errors while saving time
- Real-time reporting and accurate deal projections for better decision-making
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Reliable Data Governance at Scale
Strengthening governance through standardized workflows, automation, and compliance-focused controls for reliable data management.
Client
A leading mutual life insurance provider
Goal
Implement structured workflows to ensure reliable, compliant, and scalable data governance across complex and growing data products
Tools and Technologies
React Js, Node Js, PostgreSQL, Bitbucket, JenkinsBusiness Challenge
The organization needed to strengthen its data governance framework to handle the increasing volume and complexity of data products. Key challenges included establishing governance best practices with standardized workflows and controls, ensuring reliability and accuracy of data across multiple systems, and meeting evolving regulatory requirements. The lack of structured processes created risks to data quality, trust, and compliance, making governance modernization essential.
Solution
- Designed structured workflows to manage the lifecycle of data products with consistency and accountability
- Automated governance processes to streamline collaboration across teams and improve efficiency
- Standardized data-related tasks and controls to ensure uniformity and adherence to best practices
Outcomes
- Increased scalability and reliability of governance framework, ensuring consistent data quality
- Improved user experience with simplified and intuitive governance workflows
- Strengthened compliance through embedded controls and automated processes
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Migrating multiple databases to one streamlined source
Developing an architecture for data migration from several databases to a single, streamlined source with automated workflows, improved data analytics, execution of complex business rules, and cost savings.
Client
NOT NAMED IN PPT
Goal
Enable data migration from multiple sources to a streamlined source with automated workflows and improved data analytics
Tools and Technologies
NOT LISTED SEPARATELYBusiness Challenge
The client used a limited number of applications to source data from multiple types of databases. The outdated system slowed responses to critical requests. It also faced challenges in executing complex business rules. Owing to the lack of a centralized data warehouse, its data analytics could not deliver meaningful insights. Maintenance costs were also high.
The goal was to streamline the number of data sources, create a single store for data analytics, and reduce overall costs.
Solution
- Developed a customizable ETL architecture to pull data from any type of data source
- Created fully automated workflows using AWS Glue to transfer data between Stage, ODS and DWH instances
- Built a single source of information for data analytics
- Developed data analytics dashboards in Power BI
- Enabled system to perform complex business rules on the fly by integrating AWS Glue with stored procedures
Outcomes
- Optimized and consolidated multiple servers into three or fewer
- Reduced risk involved in maintenance of unsupported and dated database servers
- Improved data processing and data transfer by automating workflows
- Enhanced quality by using a single source of information for data analytics and applications
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Facilitating data-driven analytics and decision support
Creating a Data Lakehouse as a single source of truth with a multi-year strategy to derive insights, identify gaps, and enable fact-based decisions.
Client
An educational testing and assessment organization
Goal
To create a single data source that gives market insights, identifies gaps and facilitates a multi-year data-driven strategy
Tools and Technologies
NOT LISTED SEPARATELYBusiness Challenge
The client managed vast data from multiple sources to extract market insights. However, duplication across ~300 applications hampered analytics and adaptability. The need was to eliminate duplication and build a single trusted data source for efficient, data-driven decision making.
The goal was to eradicate duplication and create a single source of data that could be leveraged for efficient, data-driven decision making.
Solution
- Built a centralized Data Lake and Data Lakehouse as the single source of data
- Facilitated seamless data ingestion
- Created a single version of data and DataOps processes
- Streamlined governance through retirement of duplicate and mirrored databases
- Outlined a multi-year data strategy with clear foundational steps for scalability
Outcomes
- Enabled analysis and advanced analytics using a centralized data lake
- Transformed decision making into a data-driven process
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