AI Text Engines

Content Classification

Categorize text files and images according to their content.

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Content Classification engines in the Veritone cognitive engine ecosystem categorize one or more documents or text files into predefined categories based on what words the text contains. Classification examples might include Finance, Internet, News, or Real Estate, with sub-categories available for further sub-classification. Categorizing text in this way can accelerate request routing and improve records management.

Content Classification Features:

  • Multiple Language Support

    Classify text in multiple different natural languages including English, Russian, Arabic, Spanish, French, and Chinese to support a diverse user-base, workforce, or population.

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    Broad Pre-Trained Taxonomy Libraries Support

    Categorize text according to hundreds of thousands of pre-defined taxonomies and relationship frameworks by the general IAB Tech Lab Content Taxonomy Version 2.0 and the IPTC NewsCodes taxonomy for media.

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    Near Real-Time Processing

    Process text files in near real-time for use cases requiring content classification for fast analysis at scale.

  • Long-Form Text Support

    Classify short-form or long-form text in files.

  • Flexible Deployment

    Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.

  • Powered by an AI Ecosystem

    Leverage advanced content classification machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from Veritone, niche providers, and industry giants.

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