CMS are the foundation of structured data management in Brightsy AI, enabling you to define, store, and interact with custom data models.
Features & Capabilities
- Schema Definition: Create custom data structures using JSON Schema standard
- Field Validation: Enforce data integrity with type checking and validation rules
- UI Configuration: Customize how forms and data display appear to users
- Relationships: Define has-one and has-many relationships between record types
- Natural Language Search: Semantic search capabilities on enabled record types
- Advanced Querying: Complex filtering, sorting, and aggregation across records
- Vector Database Support: Enables Retrieval-Augmented Generation (RAG) applications
How to Use
Creating Record Types
{
"type": "object",
"required": ["name", "email"],
"properties": {
"name": {
"type": "string",
"title": "Name"
},
"email": {
"type": "string",
"format": "email",
"title": "Email Address"
},
"phone": {
"type": "string",
"title": "Phone Number"
}
}
}
UI Configuration
{
"name": {
"ui:autofocus": true
},
"email": {},
"phone": {
"ui:placeholder": "+1 (xxx) xxx-xxxx"
}
}
Managing Records
- Create records that conform to your schema definitions
- Query records with advanced filtering
- Update records while maintaining schema validation
- Delete records when no longer needed
Best Practices
- Field Design: Use descriptive field names and appropriate data types
- Required Fields: Only mark truly essential fields as required
- Validation Rules: Apply appropriate constraints (min/max values, patterns, etc.)
- Nested Objects: Use nested structures for logically grouped data
- Relationships: Use has-one and has-many fields to connect related record types
- Natural Language Search: Enable only on record types that benefit from semantic search
- UI Configuration: Customize form appearance for optimal user experience
Learn More
- Relationships Guide - Learn how to define and use has-one and has-many relationships
- Documentation: Add descriptions to fields to guide users during data entry