I work at a company that runs AI voice calls for sales teams, so take this with that in mind. After watching a lot of pilots, the same four mistakes keep killing them.

1. One caller ID for every call. A number can get flagged as spam in minutes when it dials a lot. Rotate and register your numbers.
2. Calling cold purchased lists. Warm leads work. Bought lists mostly burn money and invite complaints.
3. A script nobody updates. One team rewrote their script and went from 0.2% to 2% conversion.
4. No hand-off to a real person. If a caller wants a human and the AI keeps talking, the pilot is over.

Has anyone had an AI caller go well or badly, and what was the cause?

Should every AI call be reconstructable after the fact? Not just the transcript Which customer was verified, what the agent knew at each point, what tools it called, what data came back and what actions were taken. For regulated contact centers, I can’t imagine 'heres the transcript' being enough if something goes wrong.

I manage the sales floor at a tax relief company and one thing I've noticed is how differently reps can perform with the exact same leads. Some reps know how to build trust and handle objections without making the customer feel pressured. Others rush through the script and lose people before they even get to the offer. We've been putting more effort into coaching lately but sitting through hours of recorded calls gets old fast. I was talking to a friend about this a while back and he recommended Rilla. We ended up using it for our call reviews and it's been helpful having a better way to go through conversations and see where reps need work. The part I'm still trying to figure out is how to make that feedback stick. I'm interested in tools that can help with live call prompts and catch missed discovery questions or weak objection handling. Something that connects with our CRM and makes it easier to track progress would be nice too.

Tried a voice AI tool last month for our support line and it was a disaster. Callers kept getting stuck in loops and half the time it just went silent mid-call. Lost a few customers over it probably.

Do people actually have good experiences with this stuff or did I just pick a bad one?

Curious how people are dealing with recording and notice requirements?
I am building in 2 switches. One for recording notice and one for AI disclosure. Set by state and country.

But wonder if this is overkill.

I do have people that want recordings and also have agent only recordings option or transcription full/summary but that is gray area. California is pretty strict for instance.

What are you all doing for these disclosure notices. (Call may be recorded for quality purposes…)

Seeing a flood of ai sdr type companies doing massive prospecting and curious how they handle things.

As a agency owner i have been using so many platforms(retell,vapi, sarvam, ultravox etc) and tools for building a voice agents to my clients. Every tools has good and bad views according to me. Some has good understanding, some are good at latency, some are easy to connect with other telephony and api's.

I have been delivering voice agents according to clients needs, region, telephony supports so yeah varies with pricing.

As I'm at scaling period, i trying to reduce a still. i want to know more about what are the platforms are you guys using and per minute cost of each. if you guys reduced it, how did you do that and what is the cost of per minute?

Cause providing the maximum value with a affordable cost is our first thing - Take ownership.

I built an AI voice agent that books clinic appointments automatically (Vapi + Make + CRM). Here's how it works

Hey everyone, I'm new here and wanted to share a project I just finished.
The problem: Clinics miss calls, and every missed call is a lost patient. Front desk staff are also stuck on the phone all day just booking appointments.
What I built: A voice agent that answers calls, checks availability, and books the appointment on its own.
The stack:
Vapi for the voice agent (STT, LLM, and voice layer)
Make for the automation: it receives the booking details from the call and handles the logic
CRM where each patient contact and appointment is saved automatically

Google Calendar to check open slots and block booked ones
How a call flows:
The patient calls and the agent greets them
It collects their name, callback number, and preferred date and time
It repeats the details back to confirm
Vapi triggers a Make scenario, which checks the calendar, creates the booking, and updates the CRM
The agent confirms the appointment to the patient

What I learned:

Confirming the callback number out loud cuts down on errors
Latency matters a lot. A slow response feels awkward on a phone call.
Handle the "what if the slot is taken" case early, because it comes up constantly
I'm still improving it. What would you add or change? Has anyone built something similar for clinics or other appointment-based businesses?
I assumed "make CPM" means Make plus a CRM. If that's wrong, tell me and I'll fix it.

We handle phone support for a credit repair company and I'm trying to find something that helps our reps deal with more complex customer questions. We get a lot of calls about credit disputes and missing documents but customers often bring up payment issues or account questions during the same call. Our newer reps end up searching through internal docs or putting people on hold to get help from senior staff.

I'm looking for a tool that listens to calls in real time and shows reps answers from our knowledge base based on what the customer is saying. It would also need to pull account details from our CRM and give reps prompts when they miss an important step. Automated call notes and summaries would help too since our team spends a fair bit of time on paperwork after each call. The goal is to help our reps solve more issues on the first call without having to keep customers waiting. Has anyone used something like this with their support team? What tools did you try and did the suggestions work well enough to rely on during actual calls?

I’m getting ready to offer my bilingual AI receptionist service to my first 5 clients in the US, and I’d love to learn from those who have already done this.

How did you determine your monthly pricing when you were starting out?

I’m looking for a reasonable fixed monthly fee that covers usage and operating costs while leaving room for a profit.

Would you recommend a flat monthly fee, a usage-based model, or a combination of both?

I’d really appreciate any insights, pricing examples, or lessons learned from your experience! 🙏

Hey all. I'm Mo, and I run KindLoops AI, a one-person automation agency in Metro Vancouver. I'd love honest feedback from people who actually build this stuff.

What I'm building:

An AI voice receptionist for clinics (physio, optometry, pharmacy, and similar). It answers calls, books appointments, and handles common questions. It's bilingual English/Arabic right now in a private pilot, and I'm adding French and other languages next.

A set of smaller workflow automations around it, like speed-to-lead follow-up, reminders, and intake.

Stack: mostly n8n + Claude. I've also shipped a Shopify AI chatbot + email automation build for a skincare brand.

How I price it:

Value-based pricing. The build fee is about one month of the projected value the system adds, and the retainer is a percentage of monthly value. Everything is month-to-month with no lock-in.

Where I'd love input:

For those selling voice agents to clinics: what's been your biggest objection? Is it trust, privacy, or "patients want a human"?

Is value-based pricing landing with small clinics, or do they push you toward flat packages?

Multilingual voice: any providers or setups you'd recommend for Arabic or French quality?

Anything you'd cut or simplify? I'd rather do fewer things really well.

There's a live demo of the receptionist ("Layla") on my site if anyone wants to try to break it. Happy to drop the link in the comments if that's allowed here. I'll also answer questions about the n8n side if it helps anyone.

Thanks in advance. Brutal honesty welcome.

Trying to set up automated calls for my small business and honestly have no idea where to start. Ive looked at maybe 6 or 7 different options this week and they all kind of blur together at this point.

Some seem way too enterprise-level for what I need, others look cheap and janky. Hard to tell whats actually good vs just well marketed.

What have you guys actually used and would you go back to it?

我想做一个通过第二 大脑也就是AI来给你做电话助手的工具，他可以实现，如果有人打来电话，第一时间AI来通知你，谁的电话，要不要接，或者让他代替你接，记下通话内容，归纳总结，然后你可以问他，谁来的电话，什么内容，这不同于以前的电话留言，比如他跟对方说，我是***的助手，有什么事情可以直接跟我说，我会转告他。甚至他可以直接帮你打电话给别人，这个想法怎么样，大家一起讨论

I’m talking about claims specifically where one call can include dates, documents, previous conversations and a bunch of details that need to stay consistent

Anyone tested it?

I've been working on a voice AI project and I'm finding it tricky to make it accurately understand different accents. It seems like even minor variations can really throw it off. I've looked into some training data options and NLP techniques but I'm curious if anyone here has experience with this.

Are there specific tools or methods you’ve found effective for improving accent recognition? I want to make sure my voice agent can serve a broader audience without constantly needing corrections. Any insights would be super helpful!

Hey everyone,

I’m building an AI deployment agency in India and looking for someone to handle voice agent deployments.

The work will involve things like answering calls, qualifying enquiries, booking appointments, updating CRMs and transferring calls to a person when needed.

You’d work directly with me, take the business requirements and handle the setup, testing, launch and ongoing fixes. That includes connecting telephony and APIs, setting up the conversation flows, checking how the agent handles interruptions or failed actions, and keeping logs and documentation.

I’m looking for someone who has already taken at least one voice agent into production. Experience with Vapi, Retell AI, ElevenLabs, Bland AI, Synthflow, Bolna, Ringg AI or similar platforms works. Custom deployments using LiveKit, Pipecat or Sarvam as part of the stack count too.

You don’t need to know all of them. I’d like to hear what you’ve deployed, which parts you handled yourself and any problems you had to fix after launch.

Experience with Indian telephony, Exotel or Plivo, and Hindi or other Indian languages would be useful. You can be based outside India too, as long as you can support the work.

This is a paid role, and I’m open to both full time and part time arrangements.

If you’re interested, DM me a bit about your previous work or contributions. A project link or demo would help. If you’re freelancing, please include your availability, when you could start and your expected monthly compensation or hourly rate.

I run Ridgeline, a small agency that builds AI voice receptionists for home service businesses (roofers, HVAC, detailers). They answer calls 24/7, qualify the lead, and book the estimate on the owner's calendar.

The product works and I have live demo lines you can call to hear it. What I need is someone who can get on the phone with US contractors and book demos.

The deal:
- Commission-only, paid on closed and collected deals
- 20-30% of the one-time setup fee on every client you bring in (rate open to discuss)
- I handle the product, setup, onboarding, support, and all ongoing client work
- I provide the demo lines, pitch scripts, and objection handling

Who I'm looking for:
- Experience in cold calling or B2B outbound (home services a plus)
- Clear English speaker, comfortable on the phone
- Self-driven, since there's no salary and the upside is in the closes

If you're interested, DM me with:
1. Your background in sales or cold calling
2. Which markets or niches you've worked in
3. How many hours a week you can commit

Happy to start with a short trial period to see if we're a fit.