Define Your AI's Language

Create robust and predictable data structures. A solid data dictionary is the DNA of a smart, error-free AI application.

Primitive Data Types

string

For simple, flexible text, from names to descriptions.

integer

For precise whole numbers, like IDs or counters.

number

For numeric values, including decimals for prices or metrics.

boolean

For true/false values, ideal for flags and settings.

date

For dates in ISO format (YYYY-MM-DD), perfect for timestamps.

object

For nesting data structures, creating rich, complex models.

array<string>

For ordered lists of text, such as tags or roles.

array<number>

For collections of numbers, useful in series data or scores.

array<object>

For lists of complex entities, like users or sessions.

An Example in Action

Try it in the Playground
{
  "username": "string",
  "email": "email",
  "age": "integer",
  "height": "number",
  "isActive": "boolean",
  "middleName": "null",
  "birthDate": "date(YYYY-MM-DD)",
  "lastLogin": "datetime(YYYY-MM-DDThh:mm:ssZ)",
  "userId": "uuid",
  "tags": "array<string>",
  "scores": "array<integer>",
  "ratings": "array<number>",
  "permissions": "array<boolean>",
  "vacationDates": "array<date(YYYY-MM-DD)>",
  "profile": {
    "bio": "string",
    "languages": "array<string>"
  },
  "loginHistory": "array<object>"
}

Understanding Data Types for AI Integration

Why Data Types Matter

In AI integration, data types are crucial for ensuring accurate communication between your services and AI agents. Proper type definitions help AI understand the expected input and output formats, reducing errors and improving the reliability of automated interactions.

  • Prevents type mismatches and validation errors
  • Improves AI agent understanding and response accuracy
  • Enables better error handling and debugging
  • Facilitates automatic data validation and transformation

Best Practices

When defining your data dictionary, follow these best practices to ensure optimal AI integration:

  • Use descriptive field names that clearly indicate purpose
  • Include validation rules and constraints where applicable
  • Document any special formatting requirements that aren't obvious from the example.
  • Consider internationalization needs for global applications
  • Plan for future extensibility and backward compatibility

Advanced Data Modeling Features

Nested Objects

Create complex data structures with nested objects and arrays for sophisticated AI interactions.

Array Support

Handle collections of data with flexible array types for lists, tags, and multiple values.

Date & Time

Proper date and time handling with ISO format support for temporal data management.

Ready to Define Your Data?

Start building robust AI integrations with proper data definitions. Our platform makes it easy to create and manage your data dictionary.

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