Large Language Models (LLMs) have enabled businesses to build advanced AI-driven features, but navigating the many available models and optimization techniques isn't always easy.
If you’re looking to combine speech recognition (STT) and LLMs for cutting-edge voice apps, look no further! Our ultimate guide is finally here, and it’s filled with valuable strategies and hands-on insights from our work with hundreds of audio-first companies and extensive interviews with experts in AI note-taking, sales enablement and customer support.
What you'll learn:
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Speech-To-Text
Voice AI has evolved fast — from early experiments that barely handled a “hello” to today’s real-time conversational agents running across industries. Alex Casella (CTO at Thoughtly) sat down with Gladia’s CEO Jean-Louis Quéguiner to unpack the technical and operational realities of building production-grade voice agents.
Speech-To-Text
As voice agents become a core part of customer and employee experience, users need to know these AI systems are accurate, safe, and acting within boundaries. That’s especially true for enterprise-grade tools, where a rogue voice agent can severely damage relationships and create major legal risks.
Case Studies
The contact center is transforming. Traditionally defined by manual workflows, siloed data, and reactive customer service, today's Contact Center as a Service (CCaaS) platforms are embracing a new era—one driven by real-time AI and automation.
