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:
Speech-To-Text
Despite rapid advances in voice agent stacks, including speech-to-text (STT), text-to-speech (TTS), and large language models (LLMs), the real-world promise of fully autonomous voice assistants remains largely unmet.
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Speech-To-Text
Voice AI has taken a leap in 2025. From early IVR experiments that barely handled a “hello” to today’s real-time conversational agents running across industries, we've come a long way. But is it truly a solved issue?
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.
