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 The high cost of owning and maintaining outdated technologies and time-to-market for new features were adding to the business challenges.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
- 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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Get in touchCloud Data Lakehouse for Single Source of Truth
Client
A medical devices and fertility solutions company
Goal
Establish a cloud data warehouse for a single source of truth and timely month-end activities
Tools and technologies
Azure Data Factory, Azure Data Lake, Power BI, Synapse Analytics
BUSINESS CHALLENGE
The client had multiple instances of ERPs, sales systems, and warehouses built on obsolete technology and frameworks. The existing system siloed the data, resulting in inconsistent versions of the truth. The client's finance and sales teams were struggling to reconcile data offline and feed the same back into the ERPs, causing significant delays in month-end activities. As the record systems were also not synced and legacy reports were built on the interim warehouses, line managers and executive teams were not able to extract actionable and comprehensive insights. A solution to onboard and integrate new datasets on an ongoing basis was required to support the data merger and acquisition process.
SOLUTION
A transformation strategy to transform data and BI applications to MS Azure was finalized. The transformation was executed in phases and included discovery, report rationalization and foundational build of a global system of reporting.
The solution included the data ingestion process with Azure Data Factory, data storage and processing using Azure Data Lake and Synapse Analytics, reports and dashboards with Power BI. A utility to accelerate the onboarding of new data entities was conceptualized and delivered to onboard and integrate new datasets to support mergers and acquisitions.
OUTCOMES
Iris data practitioners helped the client overcome key challenges and advanced data warehousing capabilities by:
- Establishing a "single version of the truth" that enabled data-driven decisions and timely completion of month-end and other critical activities
- Delivering analytics to cash business processes, including subject areas of sales, inventory, shipping, finance, etc., on Power BI
- Facilitating the generation of actionable, insightful reports and dashboards, allowing "self-service" consumption for the business leadership
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Get in touchDigital ledger secures trading integrity
Client
Global bank's trading operations
Goal
Resolve trading transaction breaks and related regulatory issues through expandable intra-company digital ledger system
Tools and technologies
Hyperledger Fabric 1.4/2.2, Java 8, Go Language 1.8, Kafka, Node JS, Microservices, OpenShift, Dockers, Kubernetes
BUSINESS CHALLENGE
A highly-manual, paper-dependent, trading and reconciliation process was causing the accumulation of a large number of daily transaction liquidity breaks, which had been cited by federal regulators and risked a billion dollar cost impact. The lack of a robust trade audit and reconciliation process to reduce liquidity breaks and operating costs led the bank to seek an immutable system that could record and unify financial practices and be expanded to other transaction areas.
SOLUTION
Iris' solution comprised a production-ready, configurable platform using microservices and blockchain-based digital ledger architecture. It employed Smart Contracts coded with requisite business rules to facilitate front office trade booking and trade reconciliation processes. RPA was utilized to automate data mapping and testing of transactions. Preventive controls were enabled by recording intra-company transactions at their initiation using uniform booking practices, and consequently guaranteeing the term of the trade. A multi-layered infrastructure was created to support real-time, batch streaming of differing file formats. The UX was enriched through Interactive UI and automated workflows.
OUTCOMES
Iris successfully introduced a global intra-company distributed ledger and trade reconciliation system that did not exist before. With self-executing contracts matching both sides of transactions prior to feeding downstream systems, the platform ensures complete integrity at the source and reduces time and cost for all transactions. The solution also achieved:
- 30% fewer liquidity breaks
- 70% improvement in operational efficiency due to the use of RPA
- 60% reduction in business-rules configuration time, due to the smart contracts
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Get in touchSoftware transformation gets compliance for bank
Client
A global investment bank
Goal
To have a unified functional validation system for FDIC compliance
Tools and technologies
SQL Server, Sybase, Data Lake, UTM, .NET, DTA, Control-M, ALM, JIRA, Git, RLM, Nexus, Unix, WinSCP, Putty, Python, PyCharm, Confluence, Rabacus, SNS, and Datawatch
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Faster and more efficient internal analysis with highly accurate QFC open positions
- 100% compliance with timing and format of required daily QFC report submissions to the FDIC
- Significant decrease in exceptions before the platform went go-live and zeroed critical defect delivery post-go-live
- An intuitive UI dashboard reflecting the real-time status of critical underlying data volumes, leakages, job run, and other stats
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Get in touchPlatform re-engineering for operational efficiency
Banking & Financial
Re-engineering data extraction platform for increased efficiency
A legacy data extraction platform was limiting business efficiency and transaction processing capabilities. Iris system modernization and platform re-engineering platform services advanced the operational efficiency manifold.
Client
One of the top 20 brokerage banks in North America
Goal
Modernize an existing, licensed data platform to meet the increasing volume of transactions and product offerings
Tools and technologies
Python, Core Java, Oracle, ETL Framework, Apache Zookeeper, Anaconda, Maven, Bamboo, Sonar, Bitbucket
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Quicker, real-time configuration and execution of 500+ jobs for loading trade feed
- Zeroed downtime, even during the trade reference data changes
- 15% faster onboarding of the new feed or data source
- Nearly 20% faster throughput for various critical feeds with parallel processing feature
- Reduced anomalies and duplication with improved consistency
- 35-40% savings in annual third-party platform/ module license fees.
- Standardized and streamlined onboarding processes and turnaround time, scaling the operations efficiencies
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Get in touchTech stack automation expedites script development by 3x
Manufacturing
Tech stack automation expedites script development by 3x
Manual processes across the multi-technology stack were severely affecting the script development cycles in terms of time, effort and cost. Iris application agnostic Test Automation framework and DevOps integration helped the client reduce the script development time and cost significantly.
Client
A leading building supplies manufacturing company
Goal
To support 30+ applications stack for UI, E2E, APIs, performance, mobile automation along with DevOps pipeline integration
Tools and technologies
.NET Core, PeopleSoft, Salesforce, WMS, JavaScript, Angular, Foxpro, C#, Selenium, SpecFlow, RestSharp, Nunit, Mobile Center/Emulators, Allure, Jira, Azure Pipeline, GitHub
BUSINESS CHALLENGE
The client had technology stacks comprising of diverse technologies that were difficult to manage. Substantial manual effort and time were spent on integrating the checkpoints, elongating the development process. Validating end-to-end business flows across different applications was the prime challenge. Reporting processes were also scattered across the entire application stack, making it vulnerable.
SOLUTION
Iris developed a robust application agnostic Test Automation framework to support the client’s multiple-technology stacks. Following the Behavior-driven Development (BDD) approach to align the acceptance criteria with the stakeholders, we built business and application layers of the common utilities in the core framework. Our experts identified E2E business flows to validate the downstream impact of the change and automated the entire stack through the shift-left approach. Azure DevOps integration enabled a common dashboard for reporting. The client attained complete version control to track production health and enforce strong validations.
OUTCOMES
Iris Automation solution enabled the client to surpass several business goals. The key outcomes of the delivered solution included:
- ~65% Increase in automation coverage
- 100+ Pipelines for in-scope applications across multiple environments
- 3700+ Test Automation scripts execution per sprint cycle achieved across applications
- 3X Faster script development of behavior-driven test cases
- Multi-day manual test effort reduced to a few hours of automated regression
- 70% Reduction in effort
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Get in touch
How Generative AI adds business value
Generative AI can address problems that traditional approaches cannot solve,
improve customer and employee satisfaction, and boost productivity and quality.
How Generative AI adds business value
Generative AI can address problems that traditional approaches cannot solve,
improve customer and employee satisfaction, and boost productivity and quality.
Generative AI Experience
Document Intelligence
and Automation
Leverage AI-driven Q&A, document summarization, and automated data extraction to streamline the processing of large volumes of complex documents. Our solutions simplify access to critical information, enabling faster decision-making, enhanced compliance, and reduced manual effort across information-heavy documents such as policies, processes, procedures and reports
Configurable, Enterprise-ready AI Platforms
Next-generation
Conversational Assistants
Natural language interfaces across documents, data and APIs unify access to structured and unstructured information. From wealth management, insurance and commercial lending to market risk and AML, our AI-driven Virtual Assistants enable seamless access to critical insights and streamline interactions by summarizing data, automating report generation, and answering complex questions with high accuracy
AI Assistant for Software Engineering
Coding assistants are great, but what about the rest of the engineering lifecycle? An extensible Gen AI-powered software engineering toolkit, featuring browser and IDE extensions, can seamlessly integrate with repositories like GitHub and JIRA. Designed to enhance overlooked areas of the software development lifecycle, it streamlines requirement validation, test case generation, and standards conformance, improving experience, and boosting productivity and quality
Agentic AI
From business use cases to software engineering, agentic AI has significant potential to dynamically leverage Gen AI and related technologies, such as MCP and A2A, for planning and automating complex activities using multiple agents, APIs, and related resources and prompts. While initial agentic AI use cases were based on static workflows, recent frameworks and models enable handling of more complex and diverse sets of use cases
Value We Provide
Scalable Approach to
Generative AI Adoption
Our structured approach to adoption often starts with Proof of Concept in a sandbox environment, evolving to a pilot, and ultimately scaling into full production-grade solutions. We thus enable organizations to scale their use of Generative AI, empowering them to address a wide range of use cases while maximizing ROI.
Accelerating Business Impact
and Improving Decision Intelligence
We streamline workflows by integrating AI into document processing, risk analysis, compliance reporting, and customer support. Our automation solutions reduce manual effort, enhance accuracy, and enable faster decision-making across business functions.
Deep Expertise in
Enterprise AI Transformation
With extensive experience in implementing AI-driven solutions, we enable enterprises to progress beyond isolated use cases and establish scalable, secure, and responsible AI adoption. Our solutions drive efficiency across knowledge management, automation, and decision-making while ensuring seamless integration with enterprise systems.
Client Success Stories
IT modernization boosts Insurance customer base
Insurance
IT modernization boosts Insurance customer base
Existing applications and business systems of a Fortune 500 Insurance Carrier were inadequate to meet customer expectations. Iris business systems transformation solution enabled the client to deliver a consistent customer experience, improving acquisition and retention significantly.
Client
A leading American Fortune 500 Insurance Services Provider, offering insurance, investment management and other financial products and services across the Americas and 40 other countries
Business Drivers
To advance business agility and customer experience through modernized business systems
Technologies and Frameworks
C#/.NET, JAVA, DevOps, Python, NodeJS, App Services, Managed Application Support
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Infrastructure availability increased to 99%
- Optimized maintainability reduced the KYC process time by 75%
- Customer response time cut down by around 40%
- Promoter score incremented from 5 to 9 out of 10
- Customer retention improved by nearly 80%
- Customer acquisition increased by 65%
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Get in touchSFTR solution strengthened market leadership
Client
A leading provider of market data and trading services
Goal
Support complex regulatory reporting with automated solution
Tools and technologies
Java, Spring Boot, Apache Camel, CXF, Drools BRE, Oracle, JBoss Fuse, Elasticsearch, Git, Bitbucket, Sonar, Maven
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Generating additional revenue from extending the new reporting services to 17 firms.
- Beating the industry benchmark (~91%), achieving a higher transaction acceptance rate (~97%), and match reconciliation at the trade repository.
- Supporting a high throughput of 6 million transactions per hour which is scalable up to 10 million.
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Get in touchCloud transformation increases business agility
Standards & Membership
Global Standards organization increases business agility
Existing applications supporting the business were built on monolith architecture with high technical debt. Iris transformed over 15 years old monolith applications into microservices with automated integration and cloud deployment to deliver faster MVPs.
Client
A non-profit global organization responsible for developing and maintaining standards, including barcodes with over 115 local member organizations and over 2 million user companies
Business Drivers
To deliver MVPs in shorter cycles, reduce Mean Time for Ticket Resolution (MTTR), and lower the total cost of ownership
Tools and technologies
C#/.NET Core, Python/DJango, NodeJS/Express, Azure WAF, Azure APIM, App Services, Azure Kubernetes Service, Azure Monitor, Application Insights
BUSINESS CHALLENGE
SOLUTION
Azure cloud offered some of the foundational features like container orchestration, app engine, integration, API gateway, monitoring and others, making cloud-specific modernization a natural choice.
Modernization strategy involved reverse engineering of on-premise applications, domain-specific grouping the product backlogs by, adopting domain-driven design, and using open source cloud-friendly software with CI/CD pipeline. We transformed the applications to a .NET core framework using cloud-native design principles on Azure cloud. The solution was developed using Azure App Services, front door and service bus following the agile development approach with two-week sprints.
OUTCOMES
Iris helped the client realize multiple business benefits, including higher agility, resiliency and cost-efficient IT operations. Key outcomes of this cloud modernization engagement are:
- Reduction in Mean Time for Ticket Resolution (MTTR) by 30%
- Increase in application and infrastructure uptime to 99.9%
- Real-time visibility of application and infra metrics
- Enabled bi-weekly MVP delivery
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