A holistic approach that accelerates your current vision while also making you future-proof. We help you face the future fluidically.
Digital Engineering

Value-driven and technology savvy. We future-proof your business.

Intelligent Enterprise
Helping you master your critical business applications, empowering your business to thrive.
Experience and Design
Harness the power of design to drive a whole new level of success.
Events and Webinars
Our Event Series
Featured Event
21 Aug
13:00 CET - 14:00 CET
Our Latest Talk
By Kanchan Ray, Dr. Sudipta Seal
video icon 60 mins
Discover more about us,
an outstanding digital
solutions developer and a
great place to work in.
Financial information,
governance, reports,
announcements, and
investor events.
News &
press releases
Catch up to what we are
doing, and what people
are talking about.
Caring &
We care for our world.
Learn about our


Beyond agility, the convergence of technology and human ingenuity.
talk to us
Welcome to digital product engineering
Thanks for your interest. How can we help?
success story

Pre-emptive network fault detection

Using analytics and machine learning to help predict faults, minimize downtime, improve user satisfaction.
The existing fault localization & root cause analysis was reactive and required a manual analysis of log files & alarms after fault occurrence. The localization of the problem proved very complex and resulted in significant downtime.
By leveraging analytics and machine learning, we developed a pre-emptive fault detection platform that ingests different datasets like logs, SNMP traps, PM/FM counters, etc., in both batch and stream forms from multiple network elements. The machine learning models detect anomalies and predict faults after filtering and cleansing the data using data engineering principles.
The solution enables the client to maintain a high quality of service and minimize SLA violations, resulting in greater user satisfaction. It also provides dashboards to depict the health of various network elements and to monitor the identified KPIs.