Datamatics Recognized in Gartner Hype Cycle for Natural Language Technologies, 2020

By Tiera Oliver

Associate Editor

Embedded Computing Design

August 25, 2020

News

Datamatics Recognized in Gartner Hype Cycle for Natural Language Technologies, 2020

TruAI allows enterprises to extract intelligence from high volumes of high-velocity data including structured, unstructured, and multi-structured data from diverse sources.

Datamatics, a global Technology, BPM, and Digital Solutions company, announced that it is recognized in Gartner Hype Cycle for Natural Language Technologies, 2020. This report is authored by analysts Bern Elliot, Anthony Mullen, Adrian Lee, and Stephen Emmott.

It is the first year that Gartner is publishing a Hype Cycle for Natural Language Technologies (NLT). According to the report, "Recent advances in artificial intelligence and machine learning have enabled innovative approaches and advances in the field of natural language technologies. This report will assist CIOs and other enterprise leaders in assessing how and where these new opportunities and methods can best be applied."

Datamatics was recognized in this report under Text Summarization as a Sample Vendor. Datamatics has its own platform TruAI which is a comprehensive Artificial Intelligence and Cognitive Sciences solution that helps enterprises leverage use cases related to pattern detection, text & data mining, and computer vision. It allows enterprises to extract intelligence from high volumes of high-velocity data including structured, unstructured, and multi-structured data from diverse sources.

Some of the key highlights of TruAI are:

  • Supports 100+ languages including international and local Indian languages;
  • Provides a advanced cognitive platform, which is capable of learning in both supervised and unsupervised environments to discover audience sentiment, trends, and opportunities;
  • Provides a user interface and an advanced web-based visualization tools on a scalable, performant, reliable, and secure platform;
  • Provides high-performance computing that analyzes on auto-pilot or in an operator-assisted mode;
  • Uses multiple data sources, data lakes, and databases to perform contextual analysis and sequence building;
  • Provides the capability to build predictive and prescriptive models;
  • Supports high-intensity information mining, data aggregation, clustering, summarization, and indexing in real-time

For more information, visit: https://www.datamatics.com/

Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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