Introducing the Sync API

· Source: AssemblyAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, short

Summary

The new Sync API, introduced with Universal 3.5 Pro, is a hybrid HTTP API designed for applications requiring precise control over end-to-end orchestration, such as push-to-talk, IVR routing, and customized voice agents. It processes audio inputs ranging from 80 milliseconds to 120 seconds, delivering transcription within 300 milliseconds. The API supports advanced features including prompting, language steering, key terms, and crucial conversational context. Demonstrations highlight its capability to accurately format specific data like birth dates (e.g., "3 4 90" to "3/4/90"), expiration dates ("1228" to "12/28"), and addresses ("123 East Main Street, New York, New York, 11021") by leveraging contextual information. This rapid (often under 300ms, with examples at 263ms and 360ms) and simple REST API eliminates polling or session management, significantly enhancing agent experience through fast, accurate, and properly formatted transcriptions.

Key takeaway

For AI Engineers developing real-time voice agents or IVR systems, the Sync API with Universal 3.5 Pro offers a critical advantage. You can achieve sub-300ms transcription with intelligent formatting by providing conversational context, eliminating the need for complex polling or session management. This directly improves user experience and agent efficiency, allowing you to focus on orchestration rather than transcription accuracy. Consider integrating this API to streamline your voice application development.

Key insights

The Sync API offers rapid, context-aware transcription for real-time and pre-recorded audio, enhancing agent experiences with precise formatting.

Principles

Method

Send audio (80ms-120s) via HTTP API, optionally with conversation context, to receive immediate, formatted transcription within 300ms without polling or session management.

In practice

Topics

Best for: Machine Learning Engineer, CTO, VP of Engineering/Data, AI Engineer, NLP Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by AssemblyAI.