To use a single agent:
In any input box, type @ and select Semantic Analysis Engine from the agent selector. After that, enter your prompt or question. The agent will start working on your task and respond directly. To use multiple agents:
No extra steps needed—when your request needs it, the app will automatically involve a group of relevant agents to deliver the most complete answer.

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What does this agent do?

Semantic Analysis Engine helps you make sense of large amounts of text—like customer feedback, reviews, or documents. It uncovers key themes, sentiment, and hidden insights, turning unstructured language into useful business knowledge.

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Why should I use it?

Use this agent when you want to extract meaning from text, spot patterns, or understand how people feel about your brand, products, or services. It saves you hours of manual reading and delivers actionable takeaways.

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When should I use it?

  • Analyzing customer reviews, survey responses, or support tickets
  • Understanding sentiment and main topics in open-ended feedback
  • Mining documents, emails, or transcripts for insights
  • Connecting text patterns to business goals or challenges

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How does it work?

Describe your data source or analysis goals. The agent reviews the text, detects sentiment, groups topics, and identifies emerging themes. It also provides visual summaries and links insights to business implications.

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What do I get?

You’ll receive:
  • A semantic analysis report of your text data
  • Maps of language patterns and key topics
  • Sentiment insights and actionable recommendations
  • Visualization tools to make insights clear

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How do I use it in the app?

  1. In any input box, type @ and select Semantic Analysis Engine
  2. Enter your prompt or describe your text data and analysis needs
  3. The agent will review your input and respond directly with its findings

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Example

“We used Semantic Analysis Engine on thousands of customer reviews. The agent quickly surfaced main themes, tracked sentiment over time, and pinpointed what customers loved (and didn’t). We used these insights to improve our next release.”

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Tips

  • Share as much context and data as possible for deeper insights
  • Use for ongoing feedback monitoring or deep dives
  • Combine with Voice of Customer Synthesizer or Content Clarity Optimizer for richer analysis