The “no-code” revolution has made AI voicebots significantly more accessible. Non-technical teams can now launch voicebots quickly with platforms like Vapi or Bland AI and start automating customer interactions without a dedicated engineering team. In practice, running a good voicebot requires serious operational strategy. Long-term success depends
WebRTC.ventures CTO Alberto González recently joined the Software Defined Talk podcast to share insights on building voice, video, and streaming applications for enterprise use. In the conversation, he explains how WebRTC powers the real-time experiences behind many of today’s most important communication products, and why companies across
Early Voice AI deployments were built on a straightforward pattern: Speech To Text, LLM, Text To Speech. That pipeline was enough to produce compelling prototypes for customer support, sales automation, and meeting summaries. The pattern holds well until it meets a regulated environment. Telecom platforms, telehealth systems,
Over the last few years, Voice AI agents have moved quickly from experimentation into production. Early adoption centered on customer support, basic IVR modernization, sales automation, meeting summaries, and general-purpose voice assistants. These early use cases were low-stakes enough to tolerate imperfection. That is changing. Real-time Voice
