Structured Output & Function Calling

By default, AI models produce freeform text - helpful for conversation but problematic when you need to feed the output into other software. Structured output techniques constrain the model's responses to specific formats: JSON objects, XML documents, database records, or API calls. Function calling takes this further by enabling the model to request specific actions - "look up the weather in London" or "add this item to the user's basket" - returning a structured specification of which function to call and with what parameters. This is crucial for building real applications. A chatbot that can only talk is limited; one that can check your order status, update your account, or schedule a meeting is genuinely useful. The model doesn't actually execute the functions - it produces structured requests that your application code then carries out, maintaining a clean separation between the AI's reasoning and the actions taken. Most major AI providers now offer built-in support for structured outputs and function calling. For businesses, this capability is what transforms AI from a conversational novelty into a practical tool that integrates with your existing systems, databases, and workflows.