Tag Extractor Agent

The Tag Extractor agent identifies and extracts relevant tags from a given context, such as user queries, chat conversations, or documents. These tags can then be used for categorization, routing, personalization, or downstream automation. The agent supports tag mapping so that extracted values are automatically aligned with predefined dictionaries or default values.

Use Cases

  • Search & Retrieval -- Extract tags from queries to improve relevance in knowledge base or document searches.
  • Conversation Intelligence -- Identify key entities (e.g., location, product type, department) from chat transcripts.
  • Personalization -- Extract user preferences and context tags to tailor responses or recommendations.
  • Routing & Categorization -- Direct queries to the right workflows or departments based on detected tags.
  • Analytics -- Enable structured tagging of unstructured text for easier reporting and insights.

Inputs

InputTypeRequiredDescription
conversationConversationYesThe text input (e.g., chat conversation or user query) from which tags will be extracted.
tag_extraction_configsArray of Tag Extraction ConfigsYesTag dimensions with extraction rules. Each config specifies a tag dimension name and rules containing tag level, extraction key, and default value.
tag_mappingsJSONNoOptional dictionary mapping extracted tag values to different values (e.g., mapping "Band" to a dictionary value "band" with a default of "C").

Outputs

OutputTypeDescription
tagsArray of StringsExtracted tags as structured key-value pairs (e.g., Location:India:Bengaluru, Department:Sales). Includes dictionary values and defaults where applicable.

Configurations

None. Tag extraction behavior is determined entirely by the tag_extraction_configs input and optional tag_mappings.

How to Use This Agent

ticket_trigger -> convert_to_text -> tag_extractor -> intelligent_actions("Apply tags to ticket") -> workflow_output

Last updated: Jul 3, 2026