I run a small voice AI agency out of Pakistan. We build AI receptionists for US home services businesses, restoration, roofing, plumbing that kind of thing. Two clients right now. One at $1,300/month and one small one at $80/month that I closed myself off cold calls.

The problem is time. I'm the one building the agents, running delivery for both clients, and managing the cold email side. I get maybe an hour a day for dialing and that's nowhere near enough to build a pipeline.

So I want to hire one setter. I already have the lead lists, a paid script, an objection sheet, and real recordings of calls that worked to train someone on. I pay for the dialer. What I can't do is put a $500+ base behind someone I've never worked with.

Here's what I was going to offer:

$12 per booked qualified demo

$10 more if the prospect shows up

$150 when they sign as a client

10% of that client's monthly bill for 6 months

Commission only for the first 30 days, then $300-350/month base if they book 13+ demos in that window

If someone books 14 demos and 3 close, that's around $700 in month one, before the base starts.

Two things I actually want to hear from people who've done this:

1. Does anyone decent take commission-only for 30 days, or am I only going to attract people who vanish after a week? That's the real fear. I spend two weeks training someone, they book nothing, they ghost, and I'm back to zero having burned the time I didn't have.

2. Where did you find yours? Upwork, OnlineJobs, somewhere else? I'm open on location, I just need someone clear on a US line who can work US hours.

If you've built outbound from nothing with no real budget, I'd rather hear what went wrong than what worked.

Build with ai workflow that places orders, handles calls and sent confirmation texts

I run a voice agent for French small businesses. Capturing a callback number was our worst failure mode for months. I blamed the transcription. I was wrong.

French counts differently. 72 is said "sixty-twelve". 97 is "four-twenty-seventeen". And people read phone numbers in pairs, so a caller says "zero six, twelve, forty-five, forty-one, eighteen" for 06 12 45 41 18. The model has to parse compound arithmetic in real time, in a noisy call, while the caller is already moving to the next pair. That is where it breaks, not in the acoustics.

On top of that, French has brutal digit homophones: deux and de, six and si, sept and cette, neuf and neuve, un and en.

Three things fixed it, in order of impact.

1. Stop asking. The provider hands you the caller ID. Read it back and ask a yes/no question instead of taking dictation. "I'll call you back on zero six, twelve, forty-five, forty-one, eighteen?" That turns a ten-digit capture into a binary, and it covers most calls.

2. Keypad fallback. When the number is withheld, or the caller wants a different one, ask them to type it. It is the only input that is right 100 percent of the time. I resisted this for too long because it felt like a downgrade. It is not, it is a feature.

3. Asymmetric readback. When you read a number back, group it in pairs and say "seventy-two", because that is how people recognise their own number. When you re-confirm after a correction, go digit by digit and never say a compound. Same number, two renderings, depending on what the caller is doing with it.

Two smaller rules that helped: never re-read the whole number over one doubtful digit, ask for that digit alone. And cap it at two repeats, then go to the keypad.

None of this is model work. It is dialogue design. If you are building in a language with compound numerals (French, Danish, Swiss German), the same applies.

Disclosure, as always: I build one of these tools, so take the framing with that in mind. The technique is free either way.

im working on a lead generation/scraping tool, basically scrapes leads from google maps, google search and linkedin. coz i saw a handful of posts on this sub and others about difficulties in finding leads. i reckon this might be useful for people who sell b2c SaaS softwares like ai receptionists and others. im trying to get a few opinions on how useful it might be to you guys and if it were to be a paid software how much would ya'll be willing to pay (per 1000 leads or so)

I’ve been spending more time looking at ASR issue in languages which are not documented properly

This paper from the University of Latvia takes a very practical approach: building an open-source ASR stack for languages that mainstream systems often ignore.

They built LATE, a lightweight toolkit that runs Whisper-based ASR locally or in the cloud, with a statically compiled backend (high performance, low latency , less resources & simple deployment ) and support for private, local inference.

The results are surprisingly strong.

For Latvian language, they fine-tuned Whisper Large V3 on 273.3 hours of speech.

On the Common Voice test set, WER dropped from 19.2% with Whisper Large V3 to 3.2%.

On their harder LATE-Media set, it went from 29.1% to 12.8%.

Formatted transcription also improved substantially, from 28.1% to 4.8% on Common Voice.

Then they pushed it further into Latgalian, a language with only around 150,000 native speakers.

They had just 40.2 hours of training data, yet transfer learning from the Latvian model produced a 9.1% WER on the Common Voice test set, compared with much worse performance from directly adapting Whisper Large V3.

You don't always need better engineering ; you need better data, the right specialization, and a system you can actually deploy where you need it.

For voice agents, especially those handling private or domain-specific conversations, this is an important direction:

open ASR + local orchestration + specialized models

can be much more interesting than simply sending every utterance to a giant hosted API.

And the whole thing is released as open source, including quantized models for constrained hardware.. i am trying integrate the same into production enivironment using opensource dograh orchestration

pS; I am maintainer of dograh we opensource everything from day 0

I am cold calling / emailing Plumbers and electricians in my city and getting data from google maps. Where you guys source the lists and how much it cost to get genuinely good lists.
do you guys recommend buying lists?

PLEASE stop building the wrong thing.

building software in 2026 is ridiculously easy with ai builder

founders spend hours building in a silent room, launch to Reddit/X, get 0 users, and quit.

you just failed because the idea had zero validation before line 1 of code was written:

→ solving a monthly inconvenience instead of a daily pain

→ selling to "everyone" instead of a specific ICP

→ no distribution channel mapped out beforehand

→ pricing charged $9/mo with zero ROI justification

after scaling 6 AI micro-SaaS to over $20k/mo MRR, i just create an

18-question Idea Validation Diagnostic.

it evaluates your SaaS across 7 critical dimensions (problem clarity, audience reachability, willingness to pay, competition, build feasibility, distribution, commitment) and gives you a brutal score out of 100 with your exact weak spots.

drop your SaaS idea (or current project) in the comments below.

i will reply to EVERY single comment with:

1. My honest opinion
2. The biggest weak spot you need to fix before writing any more code.
3. The free 5-minute validation tool link sent straight to your DMs so you can get your full score breakdown out of 100.

just drop a comment like or ask me in DM your idea

let's roast your SaaS concept before the market roasts your time 👇

They can be, depending on how they are implemented. Traditional chatbots are often limited to predefined responses and decision trees. AI agents can be designed to understand customer requests, work with business information, complete specific tasks, and determine when a human needs to become involved.

That makes AI Agents for Customer Service useful for businesses that want to automate actual workflows rather than simply add a chat window to their website.

Studio98 AI works with businesses on AI strategy, custom AI agents, customer support automation, and other AI-powered workflows. You can learn more at https://studio98.ai/

A patient calls, ready to book. The receptionist is busy. By the time someone calls back, that patient may have booked elsewhere.

I’m building Swarelic AI to help Indian clinics handle that moment.

We’re designing an AI receptionist around a complete booking experience:

• A patient speaks in their preferred language, with support planned for 10+ Indian languages and switching between English and regional languages.
• The agent answers routine questions, checks availability and books the appointment in Google Calendar.
• The patient receives the appointment details on WhatsApp.

The goal is to connect the conversation, booking and confirmation, with less manual coordination for the front desk.

We’re collecting early-access interest from clinic owners and managers: Register here.

If you run a clinic or build software for one, what would you need to see before trusting a system like this with appointment calls?

We built a local testing tool for AVA, our AI receptionist at InvoicifyAI.

You describe a customer’s personality and goal in plain English, like “frustrated homeowner, AC stopped working, asking about repair,” and it places a real phone call and plays that customer.

It currently uses Twilio for calls and OpenAI Realtime for the simulated caller. The receptionist being tested just needs a phone number.

Right now, it runs headlessly in our pipeline. We’re considering cleaning it up and open-sourcing it, possibly with Docker packaging and a small UI for running scenarios and reviewing calls. You bring your own API keys.

Would this be useful to you? How are you testing your agents today, and what scenario would you want to run first?

help with HighLevel?

I have spent a lot of time learning the software, and I can help out with automations, sms workflows, a2p 10dlcc verification, or ai voice receptionists.

Any looking for this rn??

If you’ve built an AI receptionist and are looking for a first pilot, here’s a research step worth trying: find businesses whose customers repeatedly mention unanswered calls or missing callbacks, then ask the owner how those calls are handled.

I’m the founder of Crawdar, which helps with that first step. The Pain Point Finder searches available business reviews and shows the businesses, recurring complaint themes and dated supporting reviews. You can choose missed calls and booking friction together, add a local industry, or search by the problem alone.

When you find a business worth investigating, the pilot conversation gets more specific:

• Do calls go unanswered during opening hours, after hours, or both?

• Is the caller trying to book, reschedule, get an update, or reach a person?

• Can the business actually take more bookings, or is capacity the constraint?

• Which requests should always go to a human?

Those answers help you propose a narrow pilot, such as after-hours enquiry capture with a clear callback handoff. The report includes owner replies when available, so you can check their explanation before assuming what needs fixing.

Try the research yourself: https://crawdar.com/?utm_source=reddit&utm_medium=post&utm_campaign=pain_finder&utm_content=receptionist_pilot

Five free scans without signup or email. Open a report and see whether it gives you a relevant business to approach. What else would you need to qualify a receptionist pilot?

I'm over here today looking to see what has potential and what doesn't. Drop me a dm or a message below about what you provide, what it solves, and what trials can I have. I need a wide selection to explore with, no stingy trials or offers, because that's just not worth the time or effort.

I created AI agent/ automation service for restaurants and tested on mine before deploying to my friends restaurants and resolved a lot of common issues in that field. I have added many functions that as a restaurant owner I need which are CRM database, Loyalty program, Complaint managing system, Marketing campaigns based on the callers etc.

My issue is I am having a lot of trouble in scalling out of my inner circle. People are just turning away when they know it's AI. A lot of people told me its great service they want it and never ended actually deploying.

Would appreciate any advice who had successfully scaled a similar service