- Version 3.1
- Sold by Mphasis
ML based solution which classifies airline reviews into positive and negative sentiment categories.
Mphasis applies next generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis FrontBack™ Transformation approach. 'Front2Back' uses the exponential power of cloud and cognitive to provide hyper-personalized digital experience to clients and their customers. Mphasis Service Transformation approach helps 'shrink the core' through application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world.
ML based solution which classifies airline reviews into positive and negative sentiment categories.
Machine learning based customer complaint ticket triaging model to improve accuracy of ticket assignments and thereby improve FCR and MTTR.
An ML based solution to group a corpus of documents into clusters based on topics
The solution provides 36 months forecast of product demand using historical monthly demand data.
The solution provides 30 weeks forecast of operating expenses using historical weekly operating expense data.
The solution provides 24 hours forecast at an interval of 30 mins using historic network usage data.
The solution analyses customer characteristics to predict which customers are more likely to leave the bank.
Image analytics-based solution to classify salient surface defects in aluminium die casting.
Deep Learning based low-code solution which generates HTML, CSS, HTML-JET code from hand drawn wire frames as well as visual designs.
This Natural Language Processing based solution helps in identifying multiple intents of inbound life insurance email queries.
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