A home insurance enterprise streamlined policy administration, improving scalability and security while reducing time-to-market by 40%.
Client
A leading home insurance enterprise
Goal
Expedite go-to-market strategy by integrating the policy admin system with multiple external services while ensuring scalability, security, and compatibility
Tools and Technologies
Unqork, API gateways, REST APIs, SOAP APIs
Business Challenge
The client sought to expedite its go-to-market strategy by integrating its Policy Admin system with multiple external services.
The objective was to swiftly implement these integrations while maintaining scalability, security, and compatibility with external services, thereby accelerating the organization's time-to-market for new products.
Solution
- Efficiently created APIs and seamlessly integrated them with the existing low-code/no-code enterprise application
- Utilizing pre-built and pre-exposed API gateways, the team developed highly functional and adaptable APIs without manual coding
- Unqork facilitated the creation of both REST and SOAP APIs, seamlessly integrating with external APIs, ensuring optimal data access and distribution capabilities
Outcomes
- 40% faster time-to-market, enabling quicker product launches
- 25% increase in customer satisfaction due to improved system flexibility
- Enhanced scalability and security with seamless API integrations
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Enhanced executive dashboard for streamlined reporting
A specialty property & casualty insurer improved user experience, reduced onboarding time, and centralized reporting with a new executive dashboard.
Client
A leading specialty property & casualty insurer
Goal
Redesign the existing executive dashboard to improve user experience, streamline access to reports, and reduce manual efforts in onboarding new users and reports
Tools and Technologies
Azure, UI/UX enhancements, centralized reporting hub, SSO integration
Business Challenge
The client aimed to revamp its executive dashboard to address usability concerns and enhance functionality. Users found the system difficult to navigate due to inconsistent flow and poor design. Essential information was not easily accessible in one place, leading to inefficiencies.
Additionally, onboarding a new report or user required extensive manual effort, including database updates, script creation, and multiple service tickets, resulting in turnaround times of 1-2 days.
Solution
As a strategic solution partner, Iris reimagined the executive dashboard with a focus on user experience and operational efficiency. Key enhancements included:
- Intuitive design improvements for seamless navigation and accessibility
- Expanded functionalities such as search, sorting, filtering, favorites, most reviewed, access requests, user management, notifications, and audit trail
- Development of a centralized reporting hub that provides a single access point for all Hudson reports with a mobile-friendly interface
- Deployment on Azure for seamless accessibility and performance optimization
Outcomes
- Improved customer experience and satisfaction through a user-friendly interface
- Onboarding time for new users and reports reduced to 30 minutes
- Simplified report access with SSO integration and minimal clicks required to retrieve information
- Easier discovery and navigation of reports, with enhanced filtering and search capabilities
- Personalized user views with notifications for schedule delays or report errors
- Introduction of an admin section enabling UI-based user creation, notifications, and report access management
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Seamless self-service portal integration with FINEOS
Seamless integration of a self-service portal with FINEOS AdminSuite improved scalability, reduced processing time, and enhanced user experience.
Client
A leading insurance provider specializing in absence management solutions
Goal
Migrate data and services from a legacy platform to FINEOS while ensuring a seamless user experience and improved system reliability
Tools and Technologies
Spring Boot, APIGEE, FINEOS AdminSuite, Splunk
Business Challenge
The client aimed to migrate data and services from its legacy Group Benefits Platform Transformation (GPT) system to FINEOS AdminSuite while maintaining a consistent user interface, improving data accuracy, and ensuring minimal downtime.
The system also required enhanced automation and monitoring to streamline absence creation for agents and employees.
Solution
- Developed APIs to integrate the legacy system with FINEOS AdminSuite for seamless absence management
- Designed an interactive self-service portal, allowing users to efficiently manage absences
- Used Spring Boot for service development and APIGEE for API integration
- Implemented Splunk for real-time monitoring and log analysis to enhance system reliability
Outcomes
- Increased system scalability, reliability, and data accuracy
- Enhanced user experience with a modern, intuitive interface
- Reduced time taken to create absences, improving efficiency for agents and employees
- Faster development cycles and better monitoring, ensuring proactive issue resolution
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Streamlining policy administration with low-code development
Seamless low-code development on AWS accelerated go-to-market for policy issuance, partner integration, and agent onboarding.
Client
A leading home insurance enterprise specializing in policy administration solutions
Goal
Develop policy administration applications for partner insurance carriers with seamless third-party and home-grown app integration
Tools and Technologies
Low-Code/No-Code Platform, AWS, Agile Development, Containerization
Business Challenge
The client needed a scalable policy administration solution to support insurance carriers, integrate third-party applications, and enhance policy issuance and settlement.
The goal was to accelerate the go-to-market process for partners and agents while delivering premier services for competitive pricing and superior policy coverage.
Solution
- Designed and developed a policy administration platform using a Low-Code/No-Code application development platform on AWS
- Built three Agile Pod-based teams, each containing five members for rapid iteration and development
- Leveraged containerized development, ensuring each service had its own lifecycle for enhanced flexibility and scalability
- Established weekly release plans with feature flags to enable controlled functionality deployment in production once the business was ready to adopt
Outcomes
- 200% growth in policy issuance
- Faster onboarding for agencies and agents
- Improved efficiency and scalability in policy administration
- Accelerated go-to-market for insurance partners and agents
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Gen AI platform offers future-ready capabilities
BANKING & FINANCIAL SERVICES
Gen AI platform offers future-ready capabilities
Intuitive Generative AI platform provides AI, integration, and end-use capabilities and forward-looking roadmaps for the risk teams and business users at a leading bank.
Client
A leading North American bank
Goal
Provide a wide range of AI capabilities for various risk and business teams and avoid building fragmented, outdated systems
Tools and Technologies
Amazon Bedrock and Titan V2, pgvector, Faiss, OpenSearch, Llama 7B, Claude Sonnet 3.5 and 3.7
Business Challenge
The Enterprise Risk function at a leading North American bank initiated a Generative AI (Gen AI) solution to offer a wide range of AI capabilities, including document intelligence, summarization, generation, translation, and more.
As the project evolved through proofs of concept and pilots, a key challenge emerged: the risk of creating a fragmented ecosystem with an overwhelming array of unmanageable bespoke solutions, model integrations, and reliance on potentially outdated models and libraries.
Solution
Based on prior engagements across clients, our team delivered thought leadership around how to develop and deliver capabilities using a platform approach. We also set up a Minimum Viable Product Team to iterate on new problem areas and solution approaches. Platform development includes generalized capabilities for:
- Setting up document ingestion pipelines, with choice of parsing approaches, embedding models and vector index stores
- A factory model along with configurations for integrating new parsers, embedding models, LLM interfaces etc., to quickly bring new capabilities to the platform
- User management, SSO integration, entitlements management
- API integration to bring in information/ data from internal and external sources
- Platform support of pgvector, Faiss, OpenSearch, Amazon Titan V2, Llama 7B, Claude Sonnet 3.5, and 3.7, etc.
- Intuitive chat interface for AI Masters - designated business users trained in Prompt Engineering and other techniques to assemble new AI/Gen AI capabilities for users through configuration - and end users
Outcomes
- A future-ready Gen AI platform that can easily incorporate new capabilities and updates
- Multiple specific capabilities, called skills, for use by various risk teams and business users
- A forward-looking roadmap, including ability to compose more complex capabilities using atomic capabilities
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Data migration to cloud expedites credit risk functions
Migrating on-premises models and data to the cloud enhances financial forecasting, sensitivity analysis, and time-to-market.
Client
A leading North American bank
Goal
Migrate credit risk data and SAS-based analytics models from on-premises data warehouse to AWS to enhance functionality
Tools and Technologies
AWS Glue, Redshift, DataSync, Athena, CloudWatch, SageMaker; Apache Airflow; Delta Lake; Power BI
Business Challenge
The credit risk unit of a major bank aimed to migrate SAS-based analytics models containing data for financial forecasting and sensitivity analysis to Amazon SageMaker.
This was to leverage benefits such as enhanced scalability, improved maintenance for MLOps engineers, and better developer experience. It also sought to migrate credit risk data from a Netezza-based on-premises data warehouse to AWS, utilizing a data lake on AWS S3 and a data warehouse on Redshift to support model migration.
Solution
- Decoupled data workload processing from relational systems using the phased approach with a focus on historical migration, transformational complexities, data volumes, and ingestion frequencies of the incremental loads
- Developed a flexible ETL framework using DataSync for extracting data to AWS as flat files from Netezza
- Transformed data in S3 layers using Glue ETL and moved it to the Redshift data warehouse
- Enabled Glue integration with Delta Lake for incremental data workloads
- Built ETL workflows using Step Functions during orchestration and concurrent runs of the workflow; orchestrated the concurrent runs of workflows using Apache Airflow
- Architected data shift from Netezza to AWS, leveraging a flexible ETL framework
Outcomes
- Enhanced financial forecasting and sensitivity analysis operations with analytical models and data migrated to the AWS public cloud
- Expedited time-to-market catering to client’s downstream consumption needs through Power BI and Amazon SageMaker
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Gen AI interface enhances API productivity and UX
Integrating Generative AI technology and developer portal reduces logistics provider’s API onboarding to 1-2 days.
Client
Leading logistics services provider
Goal
Improve API functionality and developer team’s productivity and user experience
Tools and Technologies
Open AI (GPT-3.5 & 4 Turbo LLM), AWS Lambda, Streamlit, Python, Apigee
Business Challenge
A leading logistics provider offers an API Developer Portal as a central hub for managing APIs, enabling collaboration, documentation, and integration efforts, but faces limitations, including:
- Challenges to comprehend schemas, necessitating continued reliance on developers
- No means to individually search for API operations on the API Developer Portal
- Difficulties keeping track of changes in newly-released API versions
- Potential week-long delays as business analysts or product owners must engage developers to check if existing APIs can support new website functionalities
Solution
Integrating Gen AI technology with API, we provided a user-friendly chat interface for business users. Features include:
- Conversational interface for API interaction, eliminating the need for technical expertise to interact directly with APIs
- Search mechanism for API operations, query parameters, and request attributes
- Version comparison and tailored response generation
- Backend API execution according to user query needs
Outcomes
- Business users are now empowered with a chat-based interface for querying API details
- Users can seamlessly explore APIs, streamlining collaboration with the API team and reducing onboarding time to one or two days, ultimately enhancing the customer experience for all stakeholders
- Developer productivity improved with the AI-powered tools in the API Developer Portal
- Functionality is enhanced from the version comparison, individual API operation search, and tailored responses
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Order management platform transformation
Platform transformation and multi-cloud integration improve multinational publishing company's order management, time-to-market and performance.
Client
Multinational publishing, media, and educational company
Goal
Improve order management and transaction processing capabilities
Technology Tools
AWS EKS, Kong, Salesforce Commerce Cloud (SFCC), Salesforce CRM, Jenkins, Sumo Logic, Datadog
Business Challenge
The client's order management platform was complex and had scalability issues, causing poor customer experience and loss of revenue. The platform was hosted on Oracle cloud, with data stored in different repositories. Services were also hosted in the Oracle cloud, which used the BICC extract to fetch information about order details from Oracle databases. The low performance of customer-facing applications was causing latency and very high transaction processing time.
Solution
Team Iris transformed Oracle-based SOA services into six microservices and migrated them to AWS EKS for autoscaling with self-healing and monitoring capabilities.
We developed services for publishing data to Salesforce CRM for quick order processing and conversions. The BICC system for diversified information and order history was enabled with real-time integration between Oracle Fusion and materialized views for data consumption.
Post migration, these services were registered in Kong for discovery, and a CI/CD pipeline was created for deployment using Jenkins. Sumo Logic was used for monitoring the logs, and Datadog was used to observe latency, anomalies and other metrics.
Outcomes
The order management platform transformation delivered the following benefits to the client:
- System performance improved by 70%
- Transaction processing capability increased by 4x
- Order processing capabilities were enhanced by 200%
- Total cost of ownership (TCO) was reduced by 30%
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API migration benefits leading logistics company
Phased migration of Boomi APIs to Apigee helps a leading logistics company improve performance and scale without business disruption.
Client
A leader in truck transportation and logistics services
Goal
Migrate Boomi-based logistics APIs to improve performance and scalability
Technology Tools
Apigee, Boomi, Swagger, JMeter, Postman, GCP
Business Challenge
The client's existing Boomi Atom platform with logistics APIs had lifecycle and monitoring issues, with frequent and elongated downtimes, causing customer experience challenges.
The system did not support the logging of events, and API transactions were untraceable. Identifying the number of customers facing issues and incidents when APIs were not working was difficult. The absence of alerting mechanisms, scalability concerns, and the Boomi platform's high licensing costs were other critical challenges.
An optimized API governance system was required to provide an abstraction for the backend services, security, and efficiencies around rate limiting, quotas, and analytics.
Solution
Iris strategized the smooth transition of 250+ Boomi APIs, starting with 20 in the pilot phase. The entire migration was planned to occur in four waves.
First, the pseudocode of Boomi APIs was documented and reviewed. The team then developed proxies in Apigee X following a TDD (Test-driven Development) approach. A well-defined logging framework was provided to the client for capturing appropriate parameters for tracking API calls.
Seamless migration of API keys from Boomi API Management (APIM) to Apigee X apps was performed. Network routing at F5 for the individual proxies was implemented to transfer the traffic from Boomi to Apigee post migration in each wave. Process metering, monitoring, and adherence/compliance hooks were inserted into the system.
Outcomes
Our API migration solution delivered the following outcomes:
- Improved performance and scalability by 30%
- Centralized logging and alerting for both APIM and backend systems resulting in 40% MTTR (Mean Time for Ticket Resolution)
- Apigee analytics enablement for API traffic, request latency, response time, target errors, and transaction revenue analysis
- Enablement of API discovery, monetization, registration, partner onboarding, and governance
- Ability to integrate the system into the Apigee developer portal
- Eliminated Boomi licensing cost
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Brokerage platform transformation improves UX
A monolithic registered investment advisor (RIA) platform transformed into microservices helps a leading brokerage firm achieve enhanced operations and user experience.
Client
A leading U.S. brokerage firm with $1+ trillion in assets and serving 6,000+ RIAs
Goal
Resolve online platform accessibility, functionality and timeliness issues
Tools and Technologies
Angular 9, Jenkins, Pivotal Cloud Foundry, Oracle, Kubernetes, Spring, Docker
Business Challenge
Client’s existing brokerage platform supporting over 6,000 Registered Investment Advisors (RIAs) and containing information about assets valued at more than $1 trillion had accessibility issues. The high cost of owning and maintaining outdated technologies and time-to-market for new features were adding to the business challenges.
Solution
Iris transitioned the client’s monolith applications to microservices to transform the RIA platform. An open-source, cloud technical stack was leveraged to develop a single-page, micro-UI-based application. BFF (Backend for Frontend) design was applied, and Angular 9 was used to achieve superior compatibility on mobile devices.
Widgets were introduced to enable seamless transitions within third-party applications. Consolidated user views were created to track assets and their performance for a unified experience for the RIAs.
Outcomes
The RIA platform transformation enabled the client to achieve significant functional enhancements, including:
- Fully functional mobile views
- 100+ integrated third-party applications
- Instant and seamless access to client accounts
- Downtime for hot deployments of fixes brought to zero
- Technical debt decreased by 45%
- Release timelines shortened by 80%
- Issue resolution time reduced by 90%
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