Summarization engines in the Veritone cognitive engine ecosystem generate a condensed version of a text whose length is based on a preset percentage of the original text. Summarization saves valuable time and cost compared to reviewing pages and pages of files manually, and summary results can be stored in systems of record for later search and share.
Create summaries with custom lengths for your use case by setting an optional size input value to a percentage of the original text – from 0 to 50% with default set at 10%.
Process text files in near real-time for use cases requiring summarization for fast analysis at scale.
Summarize short-form or long-form text in files.
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.
Leverage advanced summarization machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from niche providers, and industry giants.