Mphasis Next Labs, the research and innovation arm of Mphasis has created an AI platform, which enables enterprises to derive fast and effective insights from structured and unstructured data.
Enterprises today face a data deluge. Policy documents, annual reports, emails, broker submissions, knowledge repositories and paper documents etc are lying across enterprise boundaries. Often times, the information is multi-structured, and inconsistent making it hard to extract and analyze the data. Connecting this data to the enterprise workflow across applications and processes proves to be a challenge. Enterprises end up spending a lot of time, money and manual effort in processing the structured and unstructured data sources.
Mphasis Next Labs’ patent-pending cognitive computing platform alleviates these pain points by providing the most contextual and accurate decisions metrics from structured and unstructured data.
The cloud-based cognitive intelligence platform named Deep Insights, is powered by the state- of- the- art algorithms in machine learning, deep learning, semantics, image analytics, graph theory, predictive analysis and natural language processing.
DeepInsights is built using R, Python, Tesseract, Keras, TensorFlow, Theano and WIT.AI. It uses analytics techniques of Machine Learning, NLP, Neural networks, deep learning, graph theory and image analytics. The underlying infrastructure is AWS and Intel Xeon Machines for running the algorithms.
A team of 25 researchers led by Dr. Jai Ganesh, VP & Head- Mphasis Next Labs developed the platform over a period of two and a half years.
The DeepInsights platform is being applied across multiple industry verticals. “We are seeing a lot of traction across verticals such as in banking, financial services, insurance, logistics and manufacturing” said Jai Ganesh, VP & Head- Mphasis Next Labs.
“DeepInsights helps enterprises improve the significantly improve the quality and accuracy of analytics while reducing the time and money spent on extracting the analytical insights. It crunches the cycle time from data to insights from days to seconds. Being a cloud-native solution, it is low capital intensive, self-running and allows a high degree of customization,” he added.
Some of the transformational use cases for DeepsInsights are automated intelligent ticket routing, compliance analytics, cognitive next best action prediction, cognitive data extraction and analytics, insurance policy document analysis, claim submission analysis, cognitive claims analytics, email analytics & routing, and predictive incident management.
The ultimate users of DeepInsights are enterprise decision makers like operations staff, data scientists, business analysts, marketing, sales, finance and IT management employees.
Next Labs is running pilot projects on DeepInsights with some of the largest banks and insurance companies in the world.
“The learning curve for DeepInsights is not too steep. Enterprises can be up and running on the platform in less than three months,” he informed.
Mphasis is taking DeepInsights into the market along with its services portfolio. “We are not offering it as a standalone product. We are embedding DeepInsights as a part of all the proposals we are taking to customers. DeepInsights is taken to the market as a set of reusable cognitive computing components,” he shared.
The pricing model of the platform is a function of the quantum of the data enterprises are processing and the degree of customization they require for building the algorithms.
Set up in March 2015, Mphasis Next Labs focuses on research and innovation on emerging and future paradigms. Its drives technology innovation of the company’s focus areas like Cognitive Computing and Cloud Computing through applied research, IP creation, and new platform and solution development.
Source: .techgig.com
Author: THE HANS INDIA
Published at: Mon, 18 Dec 2017 15:15:58 +0530
No comments:
Post a Comment