How To Build Voice AI With Adaptive Latency For Poor Network Connectivity

<p>Everyone evaluating AI avatar platforms focuses on voice quality. The bigger UX killer is almost always latency — and it's a harder problem than picking a good TTS

<p>Most developers underestimate how hard voice AI actually is.</p> <p>To build a production-ready calling agent, you need to integrate:</p> <p>– SIP signalling</p> <p>– Real-time

<p><em>By <a href="https://parvejshah.com" rel="noopener noreferrer">Parvej Shah</a> — Full-Stack Web Developer &amp; AI Systems Engineer based in Dhaka, Bangladesh.</em></p>

<p>When I was building <a href="https://intervu.dev" rel="noopener noreferrer">intervu.dev</a>, an AI mock coding interviewer that conducts full voice interviews in the browser,

<p>Most AI tutors today feel like glorified chatbots with a text-to-speech layer slapped on top. But what if students could actually <em>talk</em> to their tutor, pause

<p><strong>Something went wrong. The agent said something bizarre, or paused for three seconds, or completely misunderstood the user. The real question is: which layer broke? The

<p>Adding voice messages to an AI companion is one of those features that sounds simple until you try to ship it. "Just use a TTS API and send the audio" -sure, in theory. In

<p>I spent <strong>3-4 weeks</strong> building an AI voice agent that cold-calls HVAC owners for me. Real outbound. Real objection handling. Real appointments booked. When we