Text Analytics

Anzo makes it easy to apply best-of-breed text analytics to discover insights inside documents, emails, social media, web sites and more.

Understanding the contents of unstructured text has generally required extensive time and effort by experts to read reams of documents and manually extract key information into spreadsheets or structured databases. With Anzo’s text analytics capabilities, business analysts can set up text processing pipelines that can automatically analyze textual content by extracting entities, extracting relationships, analyzing sentiment, summarizing or classifying documents.

  • Key Benefits
  • Use Cases
  • Capabilities
  • Treat unstructured content as a first-class source of data for analysis and decision-making
  • Automate the monitoring and analysis of content from documents, emails, social media, web sites, and more.
  • Increase the accuracy and precision of analysis by applying multiple text analytics techniques at once
  • Access all information in one place—regardless of format, structure, or location
  • Assess the trustworthiness of unstructured content by tracking data lineage and recency
  • Easily navigate both explicit and implicit relationships found within unstructured content
  • A large retail bank’s call center automates call quality and compliance monitoring with Anzo’s text analytics capabilities. They replace limited sampling of call quality with automated text analytics that detects sentiment, friendliness and quality of call center interactions. 
  • A large pharma organization monitors reaction to their own and competitors’ drug launches by analyzing social media and patient forums chatter.
  • Buy-side equity analysts at an investment bank streamline their research processes by using Anzo to perform topical analysis and longitudinal forward-looking sentiment analysis for companies of interest.
  • Market research and public relations teams at an international consumer insurance company monitor social media sites for per-topic sentiment over time and integrate that information with structured data from internal customer and product repositories.
  • Find facts, entities, relationships and patterns in any documents
  • Use semantic search to discover answers across documents and structured data together.
  • Summarize a sea of documents to just the facts, paragraphs or documents relevant to what you’re doing
  • Set up text processing pipelines with an easy-to-use browser-based interface
  • Use sophisticated semantic processing to enrich text analytics results
  • Automatically translate, de-duplicate and archive documents