r/AIReceptionists

Hey folks 👋 

I’m Aman Singh, Founder at FloGPT, working on voice AI agents and conversational IVR used in real production environments inbound, outbound, and call center automation. 

We currently work with large BFSI and insurance teams in India & US, and our systems handle 10M+ voice calls every month in production. 

I’ll hang around here for the next 24 hours answering questions on things like: 

• Voice AI agents & IVR 
• What actually breaks at scale (and why) 
• BFSI / insurance use cases in India 
• Latency, ASR/TTS, barge-in, compliance 
• Infra, costs, and real deployment trade offs

 

Not here to sell anything, just sharing what we’ve learned (including mistakes 😅). 

One thing most people completely underestimate when building voice AI at scale is not the model itself, happy to explain why. 

Hi Chat! I have a cleaning business and need an Ai Receptionist to add to my tech stack ASAP.

Unfortunately, it’s been a complete struggle even getting in contact or scheduling a demo for most of the companies that people promo on here (& ask how they can get more customers…lol).

This is also concerning because if you cannot get on a call to give me a demo, then I’m assuming getting on a call for support if anything goes wrong will also be an issue.

Trials usually do not offer the full features, so without a demo to ask specific questions related to my business needs, I would have to pay for 1 month, see if it works & if not, waste more time & money testing another.

Are their any legit Ai Receptionist companies that have good customer service and are actually willing to demo their system to paying customers & have great customer support?

I would like a system that can synced with my CRM for info on my services, pricing and calendar so customers can easily receive an estimate + book. Also I would like it to be able to auto send an SMS with a link to complete the booking if the call drops. & would love different voice + tone options, and for them to sound real, not sound botty.

If so please drop recos below! I need to lock in a system ASAP.

ok the AI receptionist space has gotten really noisy in the last 18 months. every vendor's landing page sounds identical. natural voice, books appointments, 24/7 coverage, you know the script. but when you actually run one of these in a real business you find out pretty fast that most platforms fall over on the same handful of things, and the things they fall over on are usually not what the marketing site is hyping.

been watching deployments across a bunch of verticals (HVAC, dental, legal, cleaning, a few others) for a while now. here's what i've actually seen matter.

1. sub-second response latency

this is the biggest reason callers hang up on AI bots imo. there's a UX rule from the 70s/80s called the Doherty Threshold that basically says people perceive anything past about 400ms as laggy and over 1 second as broken. on a phone call it's brutal. a 2 second pause after the caller stops talking and they assume they got disconnected.

the weird thing is most platforms benchmark voice quality but not end-to-end latency. you can have the most human-sounding voice and still lose calls bc the response time is 1.8 seconds.

easy way to test: call the demo, finish a sentence, count Mississippi's. if you can get to "one Mississippi two" before it speaks, it's too slow.

2. real interruption handling

humans interrupt each other constantly on the phone. conversation analysis research out of Stanford has put interruption frequency at every 12-15 seconds in natural phone conversation. a good AI receptionist needs to stop talking the second the caller starts, and pick up where the caller actually went, not where the agent was reading from a script.

a lot of platforms either keep talking over the caller (terrible) or stop dead and ask the caller to "please repeat that from the beginning" (also terrible). both kill calls.

3. writes directly to your scheduling system

there's a Harvard / InsideSales study floating around that says leads contacted within 5 minutes are around 21x more likely to convert than at 30 minutes. but most AI receptionists "book" appointments by creating a CRM task for a human to action later. by the time someone actually looks at that task the caller's already on the phone with your competitor.

when the bot finishes the call, ask yourself: does it write directly to Google Calendar / Calendly / Jobber / HouseCall Pro / whatever you use, or does it just generate a follow-up task? if it's the second one you're basically paying for a fancier voicemail.

4. SMS recovery on dropped or abandoned calls

call abandonment in inbound business phone systems usually sits around 10-15% per ICMI's contact center benchmarks, and for AI receptionists specifically i've seen it run higher in the first 60-90 days bc people are still figuring out how to talk to one.

when a call drops at like 70-80% completion, a decent platform sends an SMS with a booking link and a "wanna finish this real quick" follow up. most platforms just lose the lead.

barely anyone talks about this feature and it's one of the bigger ROI moves on the list.

5. handles regional accents and noisy environments

ASR (the speech recognition layer) is not equal across accents. published research from MIT and Stanford has shown error rates 2-3x higher for Southern US, Boston, Scottish, Indian English, and a bunch of others vs general american english. in production this looks like the bot saying "i didn't catch that, can you repeat?" three times in a 90 second call. caller hangs up.

worth asking any vendor what ASR they use under the hood. Deepgram, AssemblyAI, Whisper, Google Speech all perform pretty differently, and most platforms don't tune for the markets your customers actually live in.

6. vertical-specific qualification flows

generic "book an appointment" flows don't really work for most service businesses. a plumber needs to triage emergency vs scheduled work first. a dental practice needs to know if it's a new patient or a recall or an emergency. a law firm needs practice area and conflict-check info. a roofer needs to separate storm/insurance jobs from retail.

most platforms ship a generic template and tell you to "customize it." in practice that means weeks of prompt engineering, and most operators don't have that kind of time. ask any vendor for a real call recording from an actual customer deployment in your vertical. not a demo. an actual production call.

7. structured data extraction into your CRM/operations stack

at the end of every call the bot should be outputting structured data into whatever you're running on the backend. as fields, not as a transcript dump. things like caller name, callback number, what they wanted, how urgent, address, preferred time.

a lot of platforms quietly skip this. they give you the transcript and assume someone will read it. but if your CSR or tech has to read 4 minutes of transcript to figure out what the caller needed, you didn't save any time, you just moved the work around.

honestly curious what other folks have run into in actual production. especially anyone deploying for the trickier verticals (legal, dental, multi-location franchises). the space still feels pretty early and right now you basically have to grill every vendor before you sign anything.

I'm going to keep this short because I hate when people pad these posts with unnecessary fluff.

I spent 8 months learning AI voice agents. Not watching. Not consuming content about it. Actually building. And failing. And building again.

Let me break down what those 8 months actually looked like.

Months 1–2: Humbling.

I thought I understood what a voice agent was. I didn't. My first few builds were genuinely embarrassing. Wrong tools firing at the wrong time. System prompts so stiff the agent sounded like a robot reading a script (which, yes, it technically is — but it shouldn't feel that way). Zero personality. Zero flow.

I almost quit twice. I didn't, and that's the only reason I'm writing this.

Months 3–4: Things started clicking.

This is where I stopped rushing and started studying individual pieces properly.

System prompts. I cannot stress this enough. This is the whole game. I rewrote mine hundreds of times — not exaggerating. After every single test call I was asking myself things like:

Does this agent sound like a human or a FAQ page? Is the tonality right for this type of client? Is the tool triggering at the right moment in the conversation or is it firing too early and killing the flow?

That level of attention is what separates a $500 freelancer from someone charging $5,000+.

Months 5–6: First real clients.

Once I got comfortable with system prompts, custom tools, API connections, and integrations — it all started compounding. I landed my first paying client. Then another.

I started at $5,000 per build. Some people reading this will think that's too high. It isn't. Not even close to what a business saves or earns when a well-built voice agent is running 24/7 handling calls, booking appointments, qualifying leads — whatever the use case is.

Months 7–8: Where I am now.

One client pays me $9,000 a month. Every month. Recurring.

Maintenance fees are charged separately on top of that because voice agents aren't set-and-forget. Prompts need updating. Integrations need monitoring. Clients ask for new features. That ongoing work is its own revenue stream.

Minimum realistic monthly earnings if you land one or two solid clients? Around $6,000. The ceiling genuinely doesn't exist if you scale.

If you want to get here, this is what you actually need:

→ Get obsessive about system prompts. Tonality, personality, trigger logic — all of it lives here.

→ Learn to build custom tools. An agent that can only talk is useless. An agent that talks and takes action is worth $5k/month to the right business.

→ Get comfortable with APIs and integrations. CRMs, calendars, databases — your client's world needs to connect to your agent's world.

→ Use Vapi. Seriously just start there and go deep on it before touching anything else.

→ Give it 3 to 4 months of real, focused, hands-on time. Not passive learning. Actual building.

That's genuinely it.

No course pitch. No funnel. I just remember being at month one thinking "why does nobody post the real breakdown of this" — so here it is.

If you're stuck somewhere in the process or want to know more about any specific part of this — system prompts, pricing, tooling, whatever — drop a comment. I check back on these.

I'm about to launch my UK based Recruitment Agency. At the beginning it will just be me solo, with staff being added alongside growth.

Initially I will be dealing with high call volumes and I need a high quality AI Receptionist that can help me filter important calls and unnecessary calls. This is important as I will get no work done if I accept every call I receive.

Would anyone have any guidance available on what AI Receptionist I should go for?

Any advice is greatly appreciated!

Our brick and mortar business gets roughly 50,000 to 55,000 phone calls a year. Almost all of them are simple calls, asking about business hours, asking where to buy tickets, asking if they need reservations, etc.

As you can imagine, it’s extremely labor intensive, especially during busy times, to respond to all these phone calls. What’s the most cost-effective place to start?

I work for a company that creates AI receptionists. My job is to sell businesses on the idea that this product is the future, which I genuinely believe it is. However, I'm curious about your thoughts: do you guys think AI will ever fully replace human receptionists? I believe this is an extremely useful tool, but an AI receptionist obviously can't get up and complete physical tasks around the office. There are some things that people will always have to do in person. Do you guys think AI can eliminate enough of the digital/phone workload to justify reducing the number of receptionists a company needs, or easily pass the remaining physical tasks off to someone else in the office? I’d love to hear how you see this tech impacting the role longterm.

I look through this sub all the time and try basically every agent I come across and I'm dumbfounded at how atrocious most of these agents are. Like they aren't even remotely production ready.

Most of them get stuck in loops, sound super annoying, and fail on like 50% of calls.

I understand the hype here has attracted a lot of "vibe-coders" looking to make a quick buck but where is the foresight?

Do these people really expect to get even a single sale, or if they do get a single sale, do they expect their clients to continue paying and not demand their money back for the "AI receptionist" that is failing on every other call and pissing off all of their customers?

For those who have actually built a well thought-out, fleshed-out, airtight solution: Any complaints you didn't expect to get after your first client?

Guys I've built my own voice AI platform, called Paladin.

I've been working on this for a couple of months optimising the latency and smoothness. And now I can say that I've built something meanwhile in terms of quality and performance wise as per the industry standard set by big players like Vapi/ Retell.

I've also managed to get initial traction by getting 3 clients from Europe but after that the journey feels stuck for me.

Can someone please guide me on this? I need genuine help on this one.

I'm also open to partnership with established agencies by providing them white labelling voice AI solution to be integrated on their client's website or use it as an AI receptionist/etc.

Hey everyone! 👋

I’ve recently built a voice AI agent that helps businesses handle calls, schedule appointments, and manage customer inquiries 24/7.

In my area, the market isn’t too saturated yet, so I’m really excited about the potential and getting this solution in front of the right people.

So far, I’ve tried cold calling but haven’t had much success, and I’d love some advice on better ways to reach potential clients or build the right connections. If you know any businesses that could benefit from this, or have suggestions on how to approach them effectively, I’d really appreciate it.

I’m serious about making this work and providing real value — this could genuinely change my life, and I’m committed to delivering great service.

Thank you so much! 🙏

I have made an Ai receptionist which is 24/7 & also I have a phone no. Which clients can call directly & talk with that demo

But my current way of getting the clients is the Cold Emails , I have been using Apollo for this sequence & Getting leads emails

Another thing I am planning is to do Cold Calls Directly, but as I live in another country - I will need to buy 19$/month Virtual No. & Then cold calls them

However I am a bit hesitant because I never did a cold call ( I am not an introvert) but I am thinking will this work or not ?

Cold emails I have sent approx 80-100 & no reply I have received.

To the people who are experienced or got some client, can you tell me how much to work on this should I increase cold email volume & Cold calls i should start ? Or am I doing anything wrong here?

We’re so focused in receptionists that handle inbound calls that nobody thinks to handle outbound calls with AI.

I implemented that for one of my clients and it drove a 44% booking rate and thousands in revenue. Why aren’t more people doing this?

Been selling an AI voice agent to plumbers, electricians, and HVAC techs for a few months now. Expected the main objection to be price. It's not. $99/month is nothing compared to what they lose in missed calls.

The real objection: "My customers are old school. They won't want to talk to a robot."

Here's what actually happens when they try it: most callers don't realize it's AI. The voice quality in 2026 is genuinely good. Natural pacing, handles interruptions, laughs at the right moments. When we tell business owners that the person who just called and booked an appointment was talking to AI, they're shocked.

The callers who DO notice it's AI? They don't care. They called because they have a leaking pipe at 10 PM. They want someone to pick up and schedule a fix. They don't care if it's a human or an AI, they care that their problem is being handled.

The only people who care that it's AI are the business owners themselves. Their customers just want the phone answered.

We started handling this objection by having the AI call the business owner during the sales conversation. They experience it as the caller. That closes the deal about 80% of the time because the objection was never based on customer feedback. It was based on assumption.

Anyone else selling AI to traditional/blue collar industries? How do you handle the "my customers won't like it" objection?

Wasn't planning to post about this but it keeps surprising me how well it works so figured I'd write it up.

Started working with a local plumber maybe 3 months ago. Good guy, been doing it like 12 years, runs a small crew. Knows his stuff. Terrible at his phone, but not in a flaky way. The man is literally under a sink with both hands on a wrench for half his day. He'd get back to his truck and there'd be 4, 5 missed calls sitting there. Half the time by the time he called back the person had already booked someone else off Google. He told me he was losing jobs every month. I kinda nodded but I had a feeling it was a lot more than that. Spoiler: it was.

So I built him an AI voice receptionist. Sounds fancier than it is honestly.

What it does is basically:

• picks up every call, doesn't matter if it's 11pm Sunday or the middle of a Tuesday
• talks like an actual person, not one of those "press 1 for emergency" nightmares
• gets the name, number, email, address, what's wrong (clog, leak, no hot water, whatever) and how urgent it is
• books straight into his Google Calendar based on what's actually open
• logs every single call into a Google Sheet
• emails the customer a confirmation
• emails him so he knows what's coming when he finally checks his phone

He doesn't touch any of it. Calls come in, jobs land on the calendar, he shows up.

The results honestly threw me off. He's booking somewhere between 5 and 7 extra jobs a week that would've been straight-up missed before. At his ticket size that's not pocket change. He told me last month was the most he's ever made and he didn't even feel busier. Just less stressed. That's actually the part he keeps mentioning. Not the money. The fact that he stopped lying awake wondering if that one missed call was a $2k water heater install or just somebody's wrong number. Now he just doesn't think about it.

Couple things I figured out along the way that might be useful if you're thinking about doing something similar: Voice quality is THE thing. Not "a thing." THE thing. We went through a few different setups before landing on one that didn't sound too robotic, with human like expressions, voice modulation depicting emotions, and intelligence with a complete knowledge base. Answering FAQs, customer support etc, this technology seems to work like an actual reciptionist, getting better every month and evolving every year. The best part of this AI is that it learns and gets better and better automatically.

The Google Sheet thing was almost an afterthought when I built it but turned out to be one of the most useful parts. He can now see every lead that ever called him, including the ones that didn't book, people who called once and never followed up, people who called outside the area, etc. He's been going back through it and texting old leads and pulling more work out of it. Wasn't expecting that.

Oh and the after-hours calls. Didn't realize how many people call plumbers at like 9pm on a Saturday until I started looking at his data. A real chunk of his extra jobs are coming from calls that hit between 6pm and 8am. Before this they all just went to voicemail and died there. I've started doing the same thing for an HVAC guy and an electrician and the pattern is exactly the same. Tradesmen are bleeding leads through their phone and most of them have no idea how bad it actually is until you put numbers on it.

Anyway. Just thought it was worth sharing. If anyone's running a service business and dealing with the same missed-call thing, the fix is genuinely not that complicated anymore.

Recently started selling AI receptionist for a company and I am new to it all. What prospecting methods/tools/systems have you found to be successful?

Hi everyone,

I’ve been working on a tool that acts as an AI receptionist for businesses. It can answer incoming calls, respond to common questions, and take booking requests automatically.

The goal is to help small businesses avoid missing customer calls when they’re busy or unavailable.

Still improving it and would like to hear any feedback from the community.

 

https://preview.redd.it/ba4oa91l4ozg1.png?width=2473&format=png&auto=webp&s=7c526c5f27bdb19a4d21388b6430a19f48bf7443

Wow, I didn't think we've reached this level yet with AI receptionist bro it took me 1min to create one. Its crazyyyyy.
What do you guys think the future of this AI voice is? Do you see it replacing real life hard workers?

Most “HIPAA-compliant” voice agent stacks stop at:
- “Our cloud signs a BAA”
- “Our STT/TTS/LLM vendors sign BAAs”
- “We encrypt in transit + at rest”

That’s necessary, but not sufficient once real PHI hits production agents.

I wrote up a short post on the gaps we keep seeing when teams assume “BAA = compliant” for AI voice agents (blog link in comments)

Quick summary of the problem areas:

- Fragmented audit trail across telephony, STT/TTS, LLM, tools, dashboards.
- LLMs treated as an unbounded PHI sink via prompts, tools, and memory.
- BAA coverage that breaks somewhere in the vendor/subprocessor chain.
- Behavioral leaks (what the agent *says* on calls) even when infra looks secure.

With Masker.dev, I’m treating PHI minimization as a first-class design constraint: sit between your voice platform and LLM, detect and redact PHI, swap in surrogates so the agent stays coherent, and keep an audit log of every redaction.

Curious how folks here are handling PHI minimization and auditability across multi-vendor voice stacks. Happy to jam in comments or DMs.

Pilar is an AI voice receptionist for trades contractors. Every missed call is a missed job. Pilar captures leads, books work, and recovers missed opportunities 24/7 so nothing falls through the cracks, all while giving you complete control over how your business runs. And unlike anything else out there, Pilar shows you exactly how much revenue it’s putting in your pocket.​​​​​​​​​​​​​​​​

- AI answers missed calls 24/7
- Flexible call answering (handles calls based on owner availability/preferences)
- Missed call SMS recovery (re engage callers who disconnected before booking or upon call failure)
- Automated booking capture
- SMS handoff to owner
- Revenue attribution dashboard (tells you exactly how much we have recovered in potential lost revenue and bringing in for your business in total)
- Pilar Listen (call transcription)-> turns human operated calls into automated bookings based off info obtained during call.
- AI Office Manager (natural language owner commands)

When you’re on the job and can’t pick up, Pilar catches it. When you’re available, you run your business exactly how you always have. We’re not trying to automate your workforce. We’re just making sure you never lose a job to a missed call again. We’re not replacing how you run your business. We’re just making sure a missed call never costs you a job again.

Looking for feedback.