Why Building Voice AI Agents Is Still So Hard (and Why We Started Dograh)

Voice AI is everywhere right now. AI phone agents, voice assistants, automated support calls. On the surface it looks like the problem is already solved. But if you actually try to build a voice AI...

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Why Building Voice AI Agents Is Still So Hard (and Why We Started Dograh)

Source: DEV Community

Voice AI is everywhere right now. AI phone agents, voice assistants, automated support calls. On the surface it looks like the problem is already solved. But if you actually try to build a voice AI agent yourself, the reality feels very different. The models are good. Speech recognition works well. Text-to-speech sounds natural. But once you start connecting all these pieces together, things get messy very quickly. Over the last few months we experimented with several voice stacks. Most of them end up looking something like this. Speech-to-text ↓ LLM reasoning ↓ Tool calls ↓ Text-to-speech ↓ Telephony Each piece works on its own. The trouble starts when you try to run the whole pipeline together in a real product. The real problems with voice AI Once we started building real voice agents, a few problems kept showing up again and again. Latency breaks the experience Voice is very different from chat. People expect responses almost instantly. Even small delays feel awkward in a conversat

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