Home Latest News Mphasis Next Labs launches InfraGraf

Mphasis Next Labs launches InfraGraf

by CIO AXIS

Mphasis today announced the launch of ‘InfraGraf’, developed by Mphasis Next Labs. The automation platform, based on powerful machine-learning, pattern recognition and graph-theory-based algorithms is a first of its kind to be launched in the industry. InfraGraf, an intelligent infrastructure automation platform, optimizes enterprise technology infrastructure investments and aids in strategic decisions-making.

Being the second solution from the Next Labs stable, InfraGraf models enterprise technology infrastructure as complex systems consisting of interconnected servers, network devices, internet of things, industrial equipment etc. The platform identifies and predicts stand-alone as well as chain of events and incidents, generate root cause analysis of incidences, failure prediction, early warning as well as cascading and ripple effect between component and machines.

“InfraGraf is a world leading intelligent infrastructure automation solution and the Next Labs team has achieved several scientific breakthroughs in terms of the algorithms and model design in areas such as temporal pattern evolution and cascading events among entities. What this means for enterprises is higher predictive and prescriptive accuracy, minimal failures and improved availability and performance”, said Dr. Jai Ganesh, Vice President & Head at Mphasis Next Labs.

“Mphasis Next Labs has a world class team that focuses on innovations in Information technology. With customer-centricity and customer relevance at the forefront, the team works towards leading the industry by bringing the best in research and innovation to our clients”, said Mr. Gopinathan Padmanabhan, President – Global Delivery and HP Channel Sales.

InfraGraf is a big data complex event processing engine which enables enterprises to innovate and make strategic decisions regarding their technology infrastructure through actionable insights by correlation and causation analysis of structured and unstructured data.

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