spammers, scammers and horrible customer support lines.
Is that really where SOTA is right now?
I attended VAPI Con earlier this year, and a lot of the discussion centered on how interruptions and turn detection are the next frontier in making voice agents smoother conversationalists. Knowing when to speak is a hard problem even for humans, but when you listen to a lot of voice agent calls, the friction point right now tends to be either interrupting too often or waiting too long to respond.
The major players are clearly working on this. Deepgram announced a new SOTA (Flux) for turn detection at the conference. Feels like an area where we'll see even more progress in the next year.
500-1000ms is borderline acceptable.
Sub-300ms is closer to SOTA.
2000ms or more means people will hang up.
ChatGPT app has a audio version of the spinner icon when you ask it a question and it needs a second before answering.
When you’re committed to phone intent complexity (hell), the AI assisted options are sort of less bad since you don’t have to explain the menu to callers, they just make demands.
Sort of like how Jira can be a streamlined tool or a prison of 50-step workflows, it's all up to the designer.
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare - in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step. - a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call. - a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
Im in this business, and used to think the same. It turns out this is a minority of callers. Some examples:
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare
I guess these are probably desperate people who are trying to get to someone, anyone. In my opinion, the best thing people can do is get a really good credit card and do a charge back for things like this.
- in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step.
I bought a Chinese wifi mesh router and it literally finds a time between two am and five am and reboots itself every night, by default. You can turn this behavior off but it was interesting that it does this by default.
- a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call.
In my defense, I've been on the other side of this. I try to avoid calling but whenever I use self service, it feels like ny settings never stick and always switch back to what they want the next billing cycle. If I have to waste time each month, you have to waste time each month.
- a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
These public websites are regularly out of date. Someone who is actually on site confirm that yes, they have non smoking rooms or ice machines that aren't broken is valuable.
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
Where is the difference between this and Indian support staff pretending to be in your vicinity by telling you about the local weather? Your version is arguably even worse because it can plausibly fool people more competently.
No, it does not cost over thirty dollars to allow someone accused to call their loved ones. We pay taxes. I want my government to use the taxes and provide these calls for free.
Example of legit calls: the pizza delivery guy decided to call my phone instead of ringing the bell, for whatever reason.
(If you do need SIP, this Asterisk project looks really great.)
Pipecat has 90 or so integrations with all the models/services people use for voice AI these days. NVIDIA, AWS, all the foundation labs, all the voice AI labs, most of the video AI labs, and lots of other people use/contribute to Pipecat. And there's lots of interesting stuff in the ecosystem, like the open source, open data, open training code Smart Turn audio turn detection model [2], and the Pipecat Flows state machine library [3].
[1] - https://docs.pipecat.ai/guides/telephony/twilio-websockets [2] - https://github.com/pipecat-ai/pipecat-flows/ [3] - https://github.com/pipecat-ai/smart-turn
Disclaimer: I spend a lot of my time working on Pipecat. Also writing about both voice AI in general and Pipecat in particular. For example: https://voiceaiandvoiceagents.com/
That’s why I created a stack entirely in Cloudflare workers and durable objects in JavaScript.
Providers like AssemblyAI and Deepgram now integrate VAD in their realtime API so our voice AI only need networking (no CPU anymore).
e.g. Deepgram (STT) via websocket -> DO -> LLM API -> TTS?
In your opinion, how close is Pipecat + OSS to replacing proprietary infra from Vapi, Retell, Sierra, etc?
Runs at around 50 cents per hour using AssemblyAI or Deepgram as the STT, Gemini Flash as LLM and InWorld.ai as the TTS (for me it’s on par with ElevenLabs and super fast)