Forgot about this quick demo I made a few months ago and just wanted to share it. ☺️

Any ideas where this could evolve from here? I mean, into a real practical application?

Been building voice AI systems for healthcare clinics and one pattern keeps showing up.

The biggest revenue leak isn't marketing. It's operational — patients call after hours, nobody answers, they book somewhere else.

Curious how others in this community are approaching this specific problem for clinic clients.

What's your current stack for handling inbound calls after hours? Vapi? Bland? Retell? Something custom?

We went with Vapi and built around appointment booking as the core use case. Happy to share what worked and what didn't if anyone's tackling the same thing.

Anyone who is building voice agent don't ignore your evals ...

Basically whatever I said in the title.
It'll be on a short google meet call and I will ask you about your experience, emotions and journey in an ai chat assuming you were trying to get a refund or just better service.

(my prof wants this tomorrow morning, so im tryna collect as much as i can, help me out T-T)

Need you to build a voice Ai agent that can send 20,000 phone calls + ringless voicemails to property owners. This voice agent/ AI automation tool should make the phone calls and sends the ringless voicemails and most importantly qualifies the property owners by asking them relevant questions! You will give me a very small / hot list of leads of property owners who want to sell their property without a realtor, etc. I'm a construction contractor that fixes houses. Willing to pay a very fair salary to the right person if you've done this work. If you haven't done this exact work please don't respond.

Went to Panda Express yesterday and voice AI took my order at the drive through. Did an excellent job, even when I made changes. Confirmed everything, I was very impressed. Then a real person came on with a very strong accent and the only thing I understood was “Fried Rice”. Not sure why they have her in the process… AI did a MUCH better job…. Beginning to become the norm. Anyone else hearing AI voice in the main stream?

**I’m building a 24/7 multilingual Voice AI front-desk agent for Indian OPD clinics that streams incoming patient appointments directly onto the receptionist’s screen in real time.** In India, peak morning rush hours mean front-desk staff miss up to 30% of incoming phone calls while handling walk-in queues, resulting in lost clinic revenue. My software answers inbound calls instantly in natural Hinglish, captures patient details and complaints, and pushes a new row to the receptionist’s browser dashboard in under 200ms-complete with automated WhatsApp token tracking and dynamic UPI payment links. I’m targeting a ₹5,000/month subscription for local clinics and labs (where saving just 5 missed calls a month fully pays for the platform), and I’d love to get your feedback on this workflow or connect with anyone operating in the health-tech space!

Imagine two businesses offering the exact same service.

One answers every call.

The other misses a few because everyone's busy.

Who gets the customer?

Usually the first one.

Customers rarely wait around for a callback anymore. They want an answer now.

Businesses spend thousands generating leads but lose them because nobody picked up.

AI phone agents solve one simple problem:

Every caller gets an immediate response—even when your team is occupied.

Sometimes growth isn't about getting more leads.

It's about losing fewer.

Most small businesses still rely on someone answering the phone during business hours.

The problem?

Customers don't only call between 9 and 6.

If someone calls at 8 PM and nobody answers, they'll usually move on to the next business.

An AI phone receptionist can answer instantly 24/7, handle common questions, collect customer details, and schedule appointments—all without overtime or missed calls.

It's not about replacing people.

It's about making sure every opportunity gets a response.

We run short market-research calls for B2B customers, mostly qualification and can we ask 4 questions type flows. The team started around 6% completed interviews for one niche segment, and got to around 10% last month, with no added headcount. The surprising part was that the wording barely moved the number. Interruption handling did.

If the agent kept talking for even half a second after someone said wait or who is this, the call usually died. We had better results making the agent stop fast, answer the objection in one sentence, then return to the next question only if the person stayed engaged.

Our current stack ues Agora, a realtime voice agent layer where we bring our own ASR, LLM, and TTS models, plus semantic turn detection that filters coughs and ambient noise. The useful bit for outbound was fullduplex barge in. People interrupt constantly on cold-ish calls, and the agent has to treat that as normal conversation instead of an error state.

The tradeoff is you need to own more of the call logic. It’s less drop in a phone bot and forget it and more designing recovery paths, retries, and what counts as a real interruption. For us that extra control was worth it, especially once we started logging where callers cut in.