Voice assistants powered by real-time AI are increasingly being used to automate phone-based customer interactions. Whether for contact centers, internal help desks, or voice-driven workflows, a reliable architecture needs to support low-latency audio streaming, accurate speech-to-text (STT), intelligent response generation, and real-time speech synthesis. In this post,
Large Language Models (LLMs) have dominated conversations about AI integration in WebRTC, particularly when it comes to voice-based features like transcription, summarization, and intent detection. But there’s an emerging layer that many outside of research circles are missing: Vision Language Models (VLMs). Unlike LLMs, which work with
The era of clunky, keypad-driven legacy IVR customer service systems that have long frustrated users is finally over. The future of Interactive Voice Response is truly conversational, and it’s ready for prime time. That’s why Deepgram’s State of Voice AI 2025 report says 84% of business leaders
Ensuring optimal Voice AI agent performance is a critical challenge for businesses deploying conversational AI. Poor voice bot interactions can lead to customer frustration, increased support costs, and lost revenue opportunities. From refining bot behavior to perfecting speech recognition and ensuring relevant responses, the journey to continuous
