Bring AI to enterprise by putting AI workbench, Data, Research and collaboration hub together.

Data Hub to fuse all data

Read data from many sources such as HDFS, HiVE, SQL server, Oracle, Neo4j, CSV and many more and write into Hadoop, Hive, Elastic search and few more. Design and built to handle massive scale data.

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Data Hub to fuse all data

Read data from many sources such as HDFS, HiVE, SQL server, Oracle, Neo4j, CSV and many more and write into Hadoop, Hive, Elastic search and few more. Design and built to handle massive scale data.

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Data Munging on massive scale data

Comprehensive Data Munging capabilities on massive scale data. Enables data scientists to understand and transform using large collection of statistical functions and distributed ETL capabilities , all with intuitive drag and drop interface.

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Data Munging on massive scale data

Comprehensive Data Munging capabilities on massive scale data. Enables data scientists to understand and transform using large collection of statistical functions and distributed ETL capabilities , all with intuitive drag and drop interface.

AI workbench and Modelling workflow

Rapidly build Machine Learning, Deep Learning and Graph Models through intuitive drag-and-drop interface. Do model ensemble and comparison by rapidly building multi branch workflow. Save the model workflow for future modification or for a scheduled run.

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AI workbench and Modelling workflow

Rapidly build Machine Learning, Deep Learning and Graph Models through intuitive drag-and-drop interface. Do model ensemble and comparison by rapidly building multi branch workflow. Save the model workflow for future modification or for a scheduled run.

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Model deployment and serving

Once developed and validated, workflows can be seamlessly deployed and scheduled for daily, weekly or any specific frequency run. The model can served to handle streaming data, mini batch data and batch data. Cutting edge input data transformation and ultra-fast scoring engine is integral part of platform.

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Model deployment and serving

Once developed and validated, workflows can be seamlessly deployed and scheduled for daily, weekly or any specific frequency run. The model can served to handle streaming data, mini batch data and batch data. Cutting edge input data transformation and ultra-fast scoring engine is integral part of platform.

Research, build and collaborate

Enables managers, data scientists and data engineers to collaborate in Model development, validation and deployment process. Not only that, once the model is built, it get published to the enterprise wide repository to be available as asset. After all, a successfully built model is one of the key asset of an organization and NT platform ensure that it remains that way.

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Research, build and collaborate

Enables managers, data scientists and data engineers to collaborate in Model development, validation and deployment process. Not only that, once the model is built, it get published to the enterprise wide repository to be available as asset. After all, a successfully built model is one of the key asset of an organization and NT platform ensure that it remains that way.

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And..Its blazing fast

NT platform is designed and built to handle massive scale data. it is blazing fast due to its in memory distributed computing architecture and every single feature on NT platform is built keeping the distributed architecture as key design principle

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