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, a pioneer in Digital Trust, today launches , an end-to-end Augmented Analytics platform that helps enterprises make faster, better decisions by leveraging Artificial Intelligence (AI) across the data value chain.Developed based on Subex's extensive data analytics experience, HyperSense contains all the Augmented Analytics capabilities enterprises need in one flexible and modular platform. HyperSense's unique no-code capabilities allow users without a knowledge of coding to easily aggregate data from disparate sources, turn data into insights by building, interpreting, and tuning AI models, and effortlessly share their findings across the orgzation.First defined by Gartner, uses enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation. It empowers experts as well as non-data scientists by automating many aspects of data science, including model development, management and deployment of AI models.AI is still in the early stages of mengful adoption in most businesses. Enterprises eager to harness the promise of AI and machine learning technology typically encounter multiple roadblocks such as demonstrating proof of value through nimble pilots; the absence of an integrated AI and data stack, and a lack of AI skills.HyperSense solves all these challenges through five powerful yet modular studios:Data Management Studio gives users one-place access to batch and streaming data across multiple data formats and lets them search, enrich, structure, and validate the data collected from across the business;Business Modelling Studio allows users to apply rules and run data audits in real-time, profile information, monitor and forecast business KPIs;AI Studio adds AI capabilities such as model building, model diagnostics, explainable AI, and hyperparameter tuning;Business Intelligence Studio visualises the data analytics output for fast insights and easy sharing;Process Automation Studio allows users to create actions and workflows to drive forward decisions based on the data insights.HyperSense also includes a number of pre-built analytics use cases in marketing, finance, and technology verticals for enterprises to deliver ultra-fast results. In addition, customers can use the HyperSense platform to build their own tailor-made, AI-powered analytics applications.The cloud-native platform can be integrated with existing data management infrastructures or implemented as a standalone, plug-and-play data analytics solution.Suresh Chintada, Chief Technology Officer, Subex, comments: "Most enterprises struggle to implement AI with business value at its centre. Instead, AI initiatives are driven by data science teams, with little alignment between the priorities of business and IT. We developed HyperSense to address this - it gives orgsations more autonomy, wider access to AI and machine learning, and puts more power into the hands of business users. With this game-changing platform, businesses will be able to truly democratise AI and turn data into reliable insights with greater speed and efficiency, supporting elastic business models and significantly accelerating their business transformation."HyperSense is a no-code, elastic, cloud-native platform built on open-source technology and can be deployed on-premises, in a hybrid infrastructure, or in any cloud environment. The platform is designed to help enterprises augment ROI from analytics and increase efficiency across the entire data value chain.This story is provided by PRNewswire. will not be responsible in any way for the content of this article. (/PRNewswire)( With inputs from ANI )Disclaimer: This post has been auto-published from an agency feed without any modifications to the text and has not been reviewed by an editor

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Business :Subex launches HyperSense, an end-to-end Augmented Analytics Platform

Subex, a pioneer in Digital Trust, today launches HyperSense, an end-to-end Augmented Analytics platform that helps enterprises make faster, better decisions by leveraging Artificial Intelligence (AI) across the data value chain. ...