Structured Outputs: Extract validated data from voice AI calls

Vapi's platform now supports structured outputs for voice AI assistants, enabling consistent data extraction that matches specified JSON schemas and eliminating parsing errors. This feature enhances the predictability and reliability of voice AI applications by ensuring data consistency, crucial for CRM updates, analytics, ML model training, and call quality control. Structured outputs allow developers to define exact schemas with types, constraints, and validation rules, resulting in validated, schema-compliant data that integrates seamlessly into application logic across different providers like OpenAI and Anthropic. This provider-agnostic implementation ensures that changing LLM providers does not disrupt data extraction workflows, while reusable schemas can be deployed across various assistants to maintain consistent data formats. The platform's structured outputs are accessible via REST API and webhooks, facilitating integration into existing systems and enabling real-time data validation. A customer spotlight on a healthcare AI platform illustrates how structured outputs have eliminated reliability issues, resulting in consistent patient data extraction for electronic health records.