The hallmark of quality

The hallmark of quality

Iris secures CMMI Level 5 Maturity appraisal for Managed Services

Iris Software has secured the CMMI Maturity Level 5 appraisal for its Managed Services operations from the CMMI Institute of Pittsburgh, Pa. The Level 5 maturity rating is the topmost awarded by the CMMI Institute, a global leader in advancing best practices in people, processes, and technology.

The CMMI Level 5 appraisal demonstrates that our teams strive to deliver better outcomes to clients by continuously upgrading capabilities and improving the quality of our processes and our application development products.

“The successful CMMI Level 5 appraisal is an important milestone in Iris’s continual efforts towards delivery excellence,” says Anil Apte, co-founder and managing director at Iris Software. “Our journey has helped us improve our performance, and that has been beneficial for the organization and our clients. The appraisal validates our commitment to quality for our clients.”

What our CMMI Level 5 rating means
  • Our work and processes have received the highest form of third party validation
  • We manage projects with an established set of practices
  • We are dedicated to continuous improvement and producing great work that makes a difference

“An appraisal at maturity level 5 indicates that an organization is performing at an ‘optimizing’ level,” according to the CMMI Institute. Organizations are recognized at that level for “continually improving their processes based on a quantitative understanding” of their business objectives and performance needs.

Such organizations are noted also for using “a quantitative approach to understand the variation inherent and the causes of process outcomes.” The five levels that the CMMI Institute has defined for its appraisals progress from “Initial, Managed, Defined, Quantitatively Managed, and Optimizing” on the maturity curve.


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Data consolidation speeds up drug search


Data consolidation speeds up drug search

An automated cloud-based consolidation application for R&D data helped a pharmaceutical company improve turnaround time for APRs and reduce manual work.


A U.S.-based pharmaceutical multinational corporation.


Reduce turnaround time for APRs.

Tools and technologies

Amazon’s AWS OPCx, Webmethods, natural language processing (NLP), neural networks, and Python programming


In pharmaceutical R&D, data is generated from several sources: the process, patients, retailers, and caregivers, among others. Pharmaceutical R&D organizations that use the traditional way of creating APRs manually consolidate paper specifications into binders across all R&D functions.

Specific regional rules, compliance mandates, and external regulations were slowing down the client’s workflow.

The many spreadsheets in multiple formats were leading to errors from manual entry and duplication of data — the inevitable “swivel effect” that results from data being pulled out from disparate, unconnected software packages.

Iris was approached to improve the process of collecting and using data from multiple sources; the improvement would help the client identify and develop new potential drug candidates faster.


Iris’s team of 12 specialists designed, developed, tested, and deployed a cloud-based application that integrates data from multiple regions and eight different systems into a single, unified interface for the client’s users. Our application unified the creation and management of the client’s workflows across its lines of business and 20 different product families.

The development environment included Amazon’s AWS OPCx; Webmethods; natural language processing (NLP); neural networks; and Python programming.


Within a year of the application’s release, 2800 users were using the application, with 55% of APRs turning around in 10 calendar weeks or less. Thanks to the in-memory data grid, the response time of transactions across-the-broad has been brought down to nearly 2 seconds.

The cloud-based application developed by Iris ensures that data is automatically and seamlessly shared between systems that were previously stand-alone and required the tedious manual entry of data.


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