Installation of business operations system to proactively monitor test pipelines, assess the potential impacts of disruptions, and provide key data insights.
Client
An educational testing and assessment organization
Goal
To develop a system that monitors business operations and provides key metrics to assess the impact of pipeline disruptions
Tools and Technologies
AWS API Gateway, AWS Lambda, AWS DynamoDB, AWS Kinesis, SQS Queue, AWS Redshift, AWS Quick Sight, MuleSoft, ServiceNow
Business Challenge
The client required a system to monitor the operations pipeline and provide a high-level overview of critical data and metrics related to test delivery and assessment. The solution needed to track registration and scoring results while also helping evaluate the potential business and financial impact of outages or disruptions.
Solution
- Developed a Business Operations Support System (BOSS) with executive and operational dashboards
- Enabled timely and accurate tracking of registration and scoring results for reporting
- Proactively monitored the operations pipeline for SLA and OLA compliance, with alerts for exceptions
- Built an operational platform to support multiple programs and act as a centralized data repository
Outcomes
- Enhanced visibility into monitoring across individual programs and domains
- Established the foundation for analytics, machine learning, automation, and intelligent forecasting in internal assessments
- Provided actionable inputs for evaluating the business and financial impact of disruptions
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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
Redshift, AWS Glue, AWS Kinesis, Apache Spark, AWS Athena, AWS Lake Formation
Business Challenge
The client managed vast amounts of data from multiple sources to extract market insights However, duplication across approximately 300 applications hampered analytics and adaptability. The goal was to eliminate duplication, identify gaps, 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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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
Major educational testing and assessment organization
Goal
Enable data migration from multiple sources to a streamlined source with automated workflows and improved data analytics
Tools and Technologies
AWS Glue, Redshift, Power BI, Oracle, MS SQL Server, MS SharePoint
Business 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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Reuters – The Future of Insurance 2026
Reuters – The Future of Insurance
Connect with Venkat Laksh, our Head of Insurance IT Sales, at the 2026 FOI forum to learn how insurers are fusing advanced, AI-driven technologies and other enterprise growth areas.
Reuters Events hosts this year’s Future of Insurance (FOI) forum on June 25-26, 2026, at the Marriott Marquis Hotel in Chicago, Illinois. FOI is a premier North American industry event where more than 500 insurance leaders come together to discuss and align key topic areas of technology, products, customers and risk. The primary themes of this year’s FOI sessions are turning strategy into growth, building the digital backbone, elevating customer experience, and ensuring risk readiness.
Iris provides Insurtech services to leading insurers, in property, casualty, specialty, life and annuity, and other sectors, that result in measurable positive outcomes in these areas. Venkat Laksh, our Head of Insurance IT Sales, is attending FOI 2026 to share Iris client success stories and the value derived from our advanced AI-powered capabilities, domain expertise, and collaborative, client-centric approach. Learn from Venkat how partnering with Iris and applying our solutions in Agentic and Generative AI/ML, Application Engineering and Modernization, Cloud and Data Engineering, can advance the digital transformation and strategic growth goals of your enterprise.
You also can contact our InsurTech team, including Abhineet Jha, Head of Insurance IT Services, and Client Partners Glenn DeGeorge, Parijat Sharma, and Vaibhav Brajesh and Delivery Partner, Mayank Khanna, to discuss your technology objectives.
Learn more about our Insurance Technology Services and Generative AI Experience.
Contact
Our experts can help you find the right solutions to meet your needs.
Get in touchAWS Summit NYC June 2026
AWS Summit NYC
Meet our team at the Summit to learn how our latest Cloud, Agentic & Generative AI, Modernization, and Data & Analytics innovations are benefiting clients in key industries.
A team of technology and domain professionals from Iris Software, an AWS partner, is attending the AWS Summit on June 17, 2026, at the Jacob Javits Convention Center in New York City. The team is excited to share insights about our latest innovations in Cloud Engineering and Migration, Agentic and Generative AI, Application and Infrastructure Modernization, and Data & Analytics. All are foundational to the digital transformation, competitiveness and growth of enterprises in nearly every industry.
The group also can discuss the measurable positive outcomes, such as enhanced security, scalability, reliability, productivity, cost-efficiency, customer experience, decision-making, and risk management and compliance, that are benefiting our clients in key sectors such as banking, anti-money laundering, insurance, financial and professional services, and logistics.
Connect with our team at the Summit or the links below to learn more about our advanced technology solutions. Our attendees include:
- Ryan Fagan - Senior Client Partner, Financial Services
- Georgy Jose - Client Partner, Enterprise Services
- Abhineet Jha - Head of Insurance IT Services
- Vaibhav Brajesh - Client Partner, Insurance IT Services
For more insights, read about our Cloud, Generative AI, and Data & Analytics services and success stories, as well as our perspective papers on Cloud Migration Challenges and Solutions, How Gen AI Can Transform Software Engineering, and Succeeding in ML Ops Journeys
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Get in touchA highly robust and reliable performance testing solution
Newly automated, AWS-based performance testing system better handles loads, bottlenecks, and SLA compliance, with near 100% reliability for the new architecture.
Client
Leading health coaching organization with a global network
Goal
To ensure automated performance testing for SLAs using a cloud-based system with near 100% reliability on new architecture
Tools and Technologies
JMeter, Datadog, AWS API Management, Dockers orchestrated with Kubernetes, Azure CDN
Business Challenge
The client’s Learning Management System and certification applications, built on a microservices-based architecture, required robust performance testing. Existing solutions struggled with encryption of APIs, varying network bandwidths, multi-region responses, and other critical parameters.
The goal was to create a cloud-based performance testing framework that could meet predefined service level agreement (SLAs), eliminate bottlenecks, ensure cost efficiency, and deliver near 100% reliability.
Solution
- Defined performance goals and identified bottlenecks
- Developed performance scripts using JMeter
- Ran bulk user load tests from three load generator machines using JMeter distributed load model
- Validated transactions across downstream applications through Validated transactions across downstream applications through load tests with an incremental and iterative approach; various network simulation techniques; load tests using Datadog APM; need-based spin-up of performance environment.
Outcomes
- Created 47 API test scripts using complex custom bean shell sampler and post processer
- Executed 30+ test cycles covering load, stress, scalability, endurance, spikes
- Identified nine critical performance bottlenecks including: middleware (API connector), database performance (mainly with indexes and orphan views)
- Automated shift left performance testing and integrated DevOps
- Ensured cost efficiency with optimized AWS ecosystem
- Enhanced overall system reliability from 73% to near 100
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A smart catalog for fast, trusted data output
Business catalog with AI-enhanced search and discovery streamlines data access, compliance and insights.
Client
An educational testing and assessment organization
Goal
To build and leverage a business catalog as a cost-effective solution for smart, user-specific output across varied datasets
Tools and Technologies
AWS Data Lake and Glue, Amazon S3 and Redshift
Business Challenge
The client needed a business catalog to enable faster discovery and better understanding of datasets in a cost-effective manner, while also generating user-specific outputs for authorized individuals. The initiative began as a pilot using a select set of data sources.
Solution
- Leveraged existing AWS Data Lake and Glue catalog for extended use
- Integrated native S3 and Redshift with the catalog
- Implemented pre-defined Glue data quality rules reporting for assets to generate a trust index before subscription
- Enhanced search and discovery with AI-generated asset metadata and summaries
- Enabled seamless authentication and authorization through SSO integration
- Automated workflow-based data access management, with human intervention only at approval stage
- Designed REST API-driven onboarding process
Outcomes
- Enabled discovery of new datasets through search and subscription
- Simplified access to reliable datasets, enhancing data science and BI for generating insights
- Established a compliance framework aligned with organizational standards
- Accelerated and improved decision-making through access to trusted data
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Quality evolution drives enterprise resilience
Quality Engineering (QE) is at an inflection point, with Gen AI and Agentic AI driving speed, resilience, and confidence at scale.
Quality evolution drives enterprise resilience
Quality Engineering (QE) is at an inflection point, with Gen AI and Agentic AI driving speed, resilience, and confidence at scale.
Quality Engineering Experience
Value We Provide
Measurable Productivity
Gains with Gen AI
Faster releases and higher engineering productivity are achieved by embedding Gen AI across test design, automation, regression optimization, and defect analytics, significantly reducing testing effort.
Predictable Quality and Reduced
Business Risk
AI-powered quality engineering improves release confidence by proactively identifying risks, reducing escaped defects, and ensuring consistent validation across platforms and distributed architectures.
Scalable, Autonomous Quality at Enterprise Level
Iris enables transition to autonomous, agent-driven quality engineering that scales across teams and geographies, supported by strong governance, responsible AI, and regulatory alignment.
Client Success Stories
ACE-FINEOS integration for enhanced absence management
Insurer attains a comprehensive absence management solution for clients by integrating APIs, upgrading data formats, and ensuring system visibility and scalability.
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
Java, Microservices, Spring Boot, APIGEE Gateway, FINEOS Admin Suite, Splunk
Business Challenge
The insurer aimed to enhance absence management capabilities for clients through the ACE (Absence Comprehensive Experience) program. This involved leveraging FINEOS, a third-party SaaS platform, to support leave plans such as: FMLA/ADA, Short- and Long-Term Disability (STD/LTD) and State-mandated Leave (SMD/PFL). Challenges included the accomplishment of seamless API integration with FINEOS; upgrading the LIMRA data-exchange format from version 1.0 to 2.0 and ensuring solution scalability.
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
- Comprehensive new absence management solution for wide range of external clients and partners
- Enhanced accuracy and interoperability with LIMRA 2.0 upgrade
- Scalable API framework to support future enhancements and client onboarding
- Enhanced system performance providing better monitoring and rapid issue resolution
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Unified platform automates investment deal data
Self-service web portal built with API integration replaces legacy SharePoint system, delivers improved UX, cost-efficiency, and real-time reporting for teams managing deals and issuer data.
Client
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 Server
Business 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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Bring the future into focus.