Properties

Properties are metadata attributes that describe and categorize content in Content Cortex. Properties provide the metadata foundation that enables AI agents to understand, classify, and retrieve content intelligently. Content Cortex supports multiple property types including binary, Boolean, string, DateTime, integer, float, ID, and object.

Properties serve as the metadata layer for agentic content management. They improve search accuracy, enable automated workflows, support compliance requirements, and facilitate content discovery. Properties also provide the structured metadata foundation that AI agents use for classification, semantic search, and intelligent content operations.

Property types

Content Cortex supports the following property types:

  • String - Text values such as document titles, author names, or descriptions
  • DateTime - Date and time values for tracking creation dates, modification dates, or deadlines
  • Integer - Whole number values for quantities or counts
  • Float - Decimal number values for measurements or amounts
  • Boolean - True or false values for flags and status indicators
  • Binary - Binary data for specialized content
  • ID - Unique identifiers for objects and references
  • Object - References to other objects for defining relationships

Single-valued and multi-valued properties

Properties can have a single value or multiple values. Single-valued properties hold one piece of information, such as a document title. Multi-valued properties store multiple related values. For example, you can define a multi-valued property named Phone Numbers that stores multiple phone numbers, such as home and cell phone numbers. You can search for objects by creating a search expression that searches for more than one value for the same property.

Object relationships

Object-valued properties define relationships between objects. For example, a Customer property can be used so that both a Loan object and a Loan Application object point to the same Customer object. This relationship model enables you to navigate between related documents and maintain data consistency.

Property configuration

Properties can be configured with default values that are set when a new object is created. This configuration reduces data entry effort and maintains consistency. The system can also restrict property values to a choice list. A choice list is a list of possible values that users select from when assigning a value to the property. Choice lists prevent data entry errors and maintain standardized terminology.

AI agent property operations

AI agents in Content Cortex interact with properties through conversational commands, enabling users to work with metadata without navigating traditional interfaces. AI agents support the following property operations:

  • View properties - Retrieve metadata such as title, author, status, dates, and custom fields without opening the document. Users can ask questions about document properties and receive immediate responses.
  • Update properties - Change metadata fields such as status, due date, or reviewer based on document content or user instructions. AI agents can analyze document content and suggest appropriate property values, or update properties according to conversational commands.
  • Suggest classification - Analyze document content and recommend the most appropriate document type. This capability ensures documents are classified correctly with the right property templates.

These AI agent operations work through the Content Cortex architecture. When a user sends a conversational request, the AI Agent plug-in communicates with the Reasoning Service, which coordinates with the MCP Server to execute GraphQL queries against the Content Platform Engine. This architecture enables natural language interaction with properties while maintaining security and governance controls.

AI agent property operations reduce task completion time by up to 70% for organizations managing large content repositories. Users can view and update document metadata through conversational commands without navigating traditional interfaces or opening documents. This natural language interaction lowers training costs, accelerates user adoption, and minimizes data entry errors that lead to compliance risks. AI agents analyze document content to suggest appropriate property values automatically, ensuring consistent classification across thousands of documents and improving content discoverability for faster decision-making. Organizations gain competitive advantage through reduced operational costs, improved content governance, and the ability to scale content operations without proportional increases in staff.