Solutions on AWS Marketplace combined with AWS Machine Learning services help users simplify data experimentation, formulate deeper insights from disparate sources across their data estate, and foster new levels of productivity and efficiency for a wide variety of use cases. Users can download free trial versions of the following Mphasis Machine Learning algorithms immediately from AWS Marketplace:
HyperGraf Influence Analytics – analyses network connection data and provides 10 key measures of influence for each actor in the network.
DeepInsights Card Fraud Analysis – a Deep-Learning powered classification solution that provides valuable insights from any data that is highly skewed with relevant class (e.g. fraudulent transactions) represented.
HyperGraf Auto Claims Prediction - provides occurrence and claim amount predictions for policyholders.
Trailer DeepInsights Trailer Capacity Prediction – helps predict volumetric capacity left in a shipping trailer.
DeepInsights Damaged Shipment Predictions - analyses images of shipment packages and assesses whether they are damaged or not.
Mphasis will add to the algorithm library on an ongoing basis.
“AWS Marketplace is helping Mphasis put the power of machine learning into the hands of developers virtually everywhere,” said Dr. Jai Ganesh -Senior Vice President & Head, Mphasis NEXT Labs. “Our solutions target practical, high-value use cases that can deliver immediate impact and ROI in critical enterprise business processes and operations. And users can deploy them with the speed and security provided by AWS.”
Mphasis is an Advanced Consulting Partner in the AWS Partner Network (APN) and leverages AWS with customers across its business. The company applies machine learning and artificial intelligence to allow companies to gain hidden value from their enterprise data. By linking datasets with cognitive computing, Mphasis helps companies accelerate process transformation and gain competitive advantage. Specific areas of expertise include:
- Cognitive Analytics - Using deep learning with neural networks, graph theory, and big data analytics to convert data to ‘smart data.’
- Contextual and Temporal Decision Making - Inferring and visualizing relationships from data to generate insights and trigger workflows for robotic process automation (RPA)
- Machine Learning - Leveraging pattern recognition, natural language processing (NLP), and machine learning for intelligent extraction of data from thousands of structured/semi-structured/unstructured file types including images, documents, PDF, and HTML
