What We Offer

Our Capabilities

Invest in smart automation, derive greater RoI

Given the heavy volume and complexity of data being shared today, integrating automated workflows and processes has become increasingly necessary in order to analyze and derive value from that data, and in a way that is as cost-effective as possible. Add unstructured data to the mix, and the intricacy multiplies.

Whether it is automating portions of a business process or automating portions of the software lifecycle, automation is everywhere and is delivering value. Aside from that, embracing intelligent automation is no longer an option today, but a critical requirement.

Agile ATDD

Acceptance test-driven development or ATDD is a methodology that helps software teams improve the quality of the product and reduce defects during testing by agreeing upon a set of acceptance criteria before development. The acceptance criteria are decided by a cross-functional team of business users and developers.  

The Iris team has developed strong capabilities in ATDD and has executed several projects using the methodology. We use a cloud-based test automation framework and have successfully automated significant parts of the ATDD process using AI-based tools.

In a typical software development project, automation is introduced in later sprints. However, Iris has been successful in bringing in automation early in the lifecycle with in-sprint automation. We have been able to achieve 90% automation even in sprints as early as sprint 1 and 2. Early automation speeds up the development process, improves quality and reduces cost.

We have shortened sprint cycles for a client by almost 90% and improved script development speed by 80% through in-sprint automation with ATDD.

Tailored solutions for financial services firms

Reorder your business model and outcomes as regulatory and compliance standards tighten.

In the context of the financial services industry, agile and digital-first fintechs have significantly disrupted and changed the playing field for traditional financial service institutions. Furthermore, increasing regulation and compliance asks are adding to their costs. Many financial services businesses are being forced to revisit their business models, drive efficiencies and productivity while maintaining a handle on lower costs.

There is a growing need for intelligent automation – one where robotic process automation (RPA) and cognitive automation join hands to drive better business and customer outcomes and experiences. The intelligent automation journey has also witnessed shifts from the more instructive, traditional rules-driven RPA to the rapidly expanding adaptive standards that process unstructured data and contextual knowledge to make decisions automatically. The next step is towards cognitive automation by mimicking human processes of perception, memory, judgment and reasoning, using adaptive algorithms.

Customers are in various stages of adopting and enhancing automation as it applies to their business and technology spectrums. They need an intelligent automation strategy where people and machines deliver the desired value to the business.

Getting ahead of the test automation curve

Automation of end-to-end processes uses technologies such as RPA, AI, ML and NLP.

Test automation is maturing. Right from the waterfall model  to the proliferation of Agile environments and shorter development cycles, testing needs to keep pace. 

With a combination of autonomous, machine learning and artificial intelligence or AI-based tools, AI is fast becoming core to every industry and function. AI-based automation enables businesses to take their software to market faster and reap consummate business benefits that accompany agility, speed and reliability.

However, most enterprises need a suitable partner to help them make the shift.

Get resilient in DevOps automation

DevOps can lower operational costs and downtimes, and minimize tech debt.

The role of automation in DevOps is crucial in value creation for the customer. It advances speed, accuracy, consistency, reliability and the number of deliveries. A resilient DevOps automation strategy encapsulates everything right from building, deploying and monitoring without delays and compromise in quality.

DevOps is acknowledged as a necessity to deliver digital capabilities at a faster rate to businesses. It is fast becoming a cultural, procedural and structural change to software development, IT and infrastructure teams that makes an immediate impact on business by lowering operational cost, reducing downtime and minimizing tech debt.

Combine it with the fact that businesses are getting increasingly software-defined, thus also having a significant bearing on DevOps. To quickly respond to changing business needs and customer feedback faster, the path to DevOps automation is also continually evolving.

Getting DevOps automation right is key. DevOps is more than implementing the right tools and technologies. The success of DevOps depends upon driving technical and cultural shifts together. Businesses need to shift from the traditional phased delivery models to a continuous delivery mindset, made possible by better integrating teams within IT and employing more automated processes. It is about developing an end-to-end perspective while embracing continuous integration and delivery. To keep the necessary integration-delivery pace, businesses need to automate as much of the testing stage as possible.

What We Offer

Automation palette

The Iris intelligent automation themes combine a range of technologies to introduce automation within the context of a function or industry to create seamless, end-to-end processes and experiences. Robotic automation when paired with machine learning and cognitive technologies, step up productivity and achieve the desired value.

Our suite of automation solutions covers intelligent automation (accelerated automation and conversational automation), test automation and DevOps automation.

Accelerated automation comprises robotic process automation (RPA) and point automation. RPA involves rules-based processes which can either be fully automated or assisted manually in case of exceptions and are typically orchestrated in standard platforms. Point automation applies to automating specific tasks at an individual user level. These are largely suited for batch operations and work queues or schedules.

Conversational automation involves automating a conversation in the form of virtual assistants for providing information, aiding in performing actions and offering recommendations with the help of natural language understanding. Here, virtual assistants engage with users in an interactive manner. They also interact with backend systems to fetch and deliver information, aid a user in completing a task and make recommendations on the basis of understanding their intent.

Cognitive extensions supplement and enhance the automation themes listed above with features such as speech to text conversion, contextual speech, and extraction from images, documents, speech and text.

Intelligent automation framework

Our intelligent automation accelerator called iASQ — Automated Service Requestor -- is a framework to build a unified omni channel interface to address service requests.

A machine learning or ML based suite of accelerator, iASQ stitches multiple channels like chatbots, email systems, collaboration platforms etc, and intelligently integrates with ITSM platforms like ServiceNow, Jira Service Desk etc. The iASQ engine is capable of handling automated triaging, adaptive capacity planning, automated resolutions, user self-service recommendations and evolving towards predicting and preventing future IT issues.

Test automation

At Iris, we have formulated various test automation approaches to enable a competitive advantage and faster realization of benefits.

Test automation for the cloud: this involves applications deployed on and for the cloud infrastructure, adopting a distributed mode of execution using cloud agents and a containerized environment for test execution.

We have capabilities to accelerate test automation, speeding up digital app release cycles and eliminating costly testing bottlenecks.

Micro-services/API test automation: A micro-services testing approach consisting of focused, small services that together create a complete application or task.

We deploy contract testing, creating and using simulators for mocking and integrating using mature REST systems.

DevOps automation boosters

Cloud-based integrations create ‘smart’ environments that lift ROI and cost savings.

We have sophisticated expertise in delivering DevOps automation solutions for financial service customers. We have undertaken complex engagements that include onboarding highly critical financial systems with customized DevOps solutions, setting up the complete DevOps pipeline with cloud-based integrations resulting in return on investment (ROI) and cost savings.

Our services portfolio provides end-to-end DevOps service with the help of best-in-class tools. We work in close collaboration with our clients to create practical high-tech solutions based on DevOps design to help organizations achieve their strategic objectives. We have undertaken complex engagements that include onboarding highly critical financial systems with customized DevOps solutions, setting up the complete DevOps pipeline with cloud-based integrations creating ‘smart’ environments that have resulted in considerable return on investment and cost savings for our customers.

We have experience in delivering DevOps solutions using technologies like Jenkins, Ansible and other technologies from leading vendors like IBM, Nexus, Pivotal, etc. Iris offers services across entire SDLC, i.e., designing and developing software, including DevOps and DevSecOps services, as well as the DevOps service alone.

The Iris advantage

We offer a mature automation practice well-versed in multi-channel, cloud application and agile work environments. We have established strengths in adaptive and cognitive automation using a combination of technology approaches including robotic process automation (RPA), natural language processing, machine learning, deep learning and reinforced learning strengths.

  • 25 + years of experience providing automation services in complex engagements in financial services
  • Maturity in ATDD with 90% automation in each sprint
  • 70% resources with Agile, DevOps and cloud experience
  • SDET qualified automation professionals
  • Expertise with developing NextGen DevOps solutions


Our experts can help you find the right solutions to meet your needs.

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