u/Solemn_Treat_854

Push too many calls too fast on a brand new number and carriers flag it as spam. Then the number is dead and the client's campaign is stuck.

So I'm trying to figure out the warm-up part.

If you've run real volume on your own numbers:

- How many calls do you make on day 1 with a new number?

- How long before you're at full volume?

- What daily limit do you stick to per number?

Also curious what actually gets a number flagged. Is it the number of calls, or is it more about people hanging up fast and not answering?

We're on SIP trunking, mostly Indian numbers with some international. Would rather learn this from someone who has already burned a few numbers than find out mid campaign.

Happy to share what we see on our side once we have real data.

Every week someone builds a voice agent and posted about it. Cool demo, nice latency numbers, no client.

I want to hear from the people who got past that. Sold it, deployed it, and have results they can point to.

Four questions. Answer all four or don't bother:

1. What was the client's actual problem?
2. What did you build for them?
3. What did you charge?
4. What results did the deployment produce?

I'll go first.

Problem: A restaurant in Valencia, Spain was losing reservations during service. Phone rings mid-rush, nobody picks up, the caller books somewhere else.

Built: Sofia - an inbound agent handling reservations and FAQs. LiveKit, Deepgram for STT, Cartesia for TTS, Plivo for SIP, Supabase on the backend, plus an analytics dashboard so the owner can see every call.

Charged: $350/month (This was my first client months ago, so charged lower)

Results: Saved them roughly 10hrs a week and got 10 more customers after 14 days.

Every week this sub gets another "I built a voice agent" post. Cool demo, nice latency numbers, no client.

I want to hear from the people who got past that. Sold it, deployed it, and have results they can point to.

Four questions. Answer all four or don't bother:

1. What was the client's actual problem?
2. What did you build for them?
3. What did you charge?
4. What results did the deployment produce?

I'll go first.

Problem: A restaurant in Valencia, Spain was losing reservations during service. Phone rings mid-rush, nobody picks up, the caller books somewhere else.

Built: Sofia - an inbound agent handling reservations and FAQs. LiveKit, Deepgram for STT, Cartesia for TTS, Plivo for SIP, Supabase on the backend, plus an analytics dashboard so the owner can see every call.

Charged: $350/month (This was my first client months ago, so charged lower)

Results: Saved them roughly 10hrs a week and got 10 more customers after 14 days

Most voice AI content stops at the demo. The hard part starts after that.

I recently shipped an outbound calling system for an online education platform. Reactivation calls to inactive students, running against their live course data.

Stack: LiveKit for orchestration, Deepgram Nova-3 for STT, GPT-4o-mini for the reasoning layer, Cartesia Sonic-3 for TTS, Plivo for SIP, Supabase for state, plus a dashboard for call analytics.

Things that actually ate time:

Latency budgeting. Every hop adds up and the person on the other end feels it before you see it in logs.

Interruptions on outbound. People talk over an agent that called them far more than one they called. Barge-in handling is not optional here.

What the LLM is allowed to see. In our case the model never receives the student's name or phone number. The greeting is stitched locally, the agent just says "you". Big drop in PII exposure for almost no effort.

Eligibility logic. Calling someone who already finished the course is worse than not calling at all. A real chunk of the build was just verifying the person is still in the state we think they're in before the dialer fires.

Campaign design. We collapsed a messy pile of filters into two campaigns, one intent each. Fewer, clearer campaigns beat clever segmentation.

Drop your questions below. Architecture, model choice, telephony, prompt structure, what falls apart at volume, cost per call, whatever you're stuck on. I'll answer what I can and tell you where client confidentiality stops me.

Not selling anything, not linking anything.

I am targeting indian edtech companies for Voice AI, and I stuck on pricing plan. For now I have created pricing tiers like:-

growth -- 0-1k mins -- 19k INR

starter -- 1-5k mins -- 37k INR

scale -- 5-10k mins -- 68k INR

with 3rs/min and rest is profit margins. I have built my own infra so everything is covered in 3rs/min. I am not sure how to price this and how do I justify it when someone on the call asks for it.

open to feedback from anyone who has done it already.

Repost to more communities

I am targeting indian edtech companies, and I stuck on pricing plan. For now I have created pricing tiers like:-

growth -- 0-1k mins -- 19k INR

starter -- 1-5k mins -- 37k INR

scale -- 5-10k mins -- 68k INR

with 3rs/min and rest is profit margins. I have built my own infra so everything is covered in 3rs/min. I am not sure how to price this and how do I justify it when someone on the call asks for it.

open to feedback from anyone who has done it already.

I am looking to a hire a CLOSER for my voice AI agency.
We have the tech and few leads and want to convert them. Just need someone who can close.

We are targeting indian edtech companies for voice AI and automation solutions for inbound/outbound.

But I’m not sure how to have an agreement with the closer? How to pay him on commission basis?

Since selling in india our pricing structure is looks like
For 1000 mins - 15k INR
For 5000 mins - 30k INR and so on

With less margins how do I hire someone? And firstly am I charging lower?

I am looking to a hire a CLOSER for my voice AI agency.
We have the tech and few leads and want to convert them. Just need someone who can close.

We are targeting indian edtech companies for voice AI and automation solutions for inbound/outbound.

But I’m not sure how to have an agreement with the closer? How to pay him on commission basis?

Since selling in india our pricing structure is looks like
For 1000 mins - 15k INR
For 5000 mins - 30k INR and so on

With less margins how do I hire someone? And firstly am I charging lower?

Been doing outbound for a voice AI offer targeting service businesses and I'm trying to sharpen my on-call process. Not looking for theory - genuinely curious how people who are closing deals actually structure things. I'm catering to Indian clients.

A few things I'd love to hear about:

Discovery -- What questions do you ask to figure out if someone's actually a fit? How deep do you go before pitching? Do you have a specific sequence or does it flow naturally?

How to build trust?

Handling the "what is this exactly" moment -- When you're selling something technical or unfamiliar (AI, automation, anything that needs explaining), how do you explain it without losing them?

The close -- Are you going for a decision on the first call or booking a follow-up? What does your close actually sound like word-for-word?

Objections - Price, "I need to think about it", "send me info" - what's your actual playbook for these?

I've been testing a few approaches but feel like I'm leaving money on the table somewhere in the middle of the call. Would love to hear what's actually working for people right now, not textbook stuff

Been doing outbound for a voice AI offer targeting service businesses and I'm trying to sharpen my on-call process. Not looking for theory - genuinely curious how people who are closing deals actually structure things. I'm catering to Indian clients.

A few things I'd love to hear about:

Discovery -- What questions do you ask to figure out if someone's actually a fit? How deep do you go before pitching? Do you have a specific sequence or does it flow naturally?

How to build trust?

Handling the "what is this exactly" moment -- When you're selling something technical or unfamiliar (AI, automation, anything that needs explaining), how do you explain it without losing them?

The close -- Are you going for a decision on the first call or booking a follow-up? What does your close actually sound like word-for-word?

Objections - Price, "I need to think about it", "send me info" - what's your actual playbook for these?

I've been testing a few approaches but feel like I'm leaving money on the table somewhere in the middle of the call. Would love to hear what's actually working for people right now, not textbook stuff.

I’ve been in voice automation AI for a while now and one thing that keeps coming up is figuring out which niches are genuinely converting vs which ones just sound good on paper. I’ve tried going after real estate and healthcare, which helped a bit but still hits a wall when it comes to budget objections and decision-maker access. Also tried e-commerce and logistics, but the sales cycles are longer than expected and POCs drag on forever.

Curious how others here handle this - is there a better niche or vertical that’s worked for you? Would love to know:

• What industry are you selling voice AI into right now (India-based or globally)?

• Is the demand different between Indian clients vs international ones?

• How are you actually finding and qualifying leads - cold outreach, LinkedIn, communities, agencies, referrals?

Would love to hear what’s actually worked, and what’s completely failed.​​​​​​​​​​​​​​​​ And how much are you charging ?

I’ve been in voice automation AI for a while now and one thing that keeps coming up is figuring out which niches are genuinely converting vs which ones just sound good on paper. I’ve tried going after real estate and healthcare, which helped a bit but still hits a wall when it comes to budget objections and decision-maker access. Also tried e-commerce and logistics, but the sales cycles are longer than expected and POCs drag on forever.

Curious how others here handle this - is there a better niche or vertical that’s worked for you? Would love to know:

• What industry are you selling voice AI into right now (India-based or globally)?

• Is the demand different between Indian clients vs international ones?

• How are you actually finding and qualifying leads - cold outreach, LinkedIn, communities, agencies, referrals?

Would love to hear what’s actually worked, and what’s completely failed.​​​​​​​​​​​​​​​​ And how much are you charging ?

I’ve been in voice automation AI for a while now and one thing that keeps coming up is figuring out which niches are genuinely converting vs which ones just sound good on paper. I’ve tried going after real estate and healthcare, which helped a bit but still hits a wall when it comes to budget objections and decision-maker access. Also tried e-commerce and logistics, but the sales cycles are longer than expected and POCs drag on forever.

Curious how others here handle this - is there a better niche or vertical that’s worked for you? Would love to know:

• What industry are you selling voice AI into right now (India-based or globally)?

• Is the demand different between Indian clients vs international ones?

• How are you actually finding and qualifying leads - cold outreach, LinkedIn, communities, agencies, referrals?

Would love to hear what’s actually worked, and what’s completely failed.​​​​​​​​​​​​​​​​ And how much are you charging ?

I've been running an AIagency with just my co-founder for a while now and one thing that keeps coming up is how to build a client fulfillment and delivery process that doesn't break when we scale.

I've tried setting up basic automations and project boards, which helped a bit but still leaves us doing too much manual admin and back-and-forth communication. Also tried standardizing our initial onboarding, but it doesn't solve the project management bottlenecks that happen during the actual delivery phase.

Curious how others here handle this , is there a better system or tool or habit that's worked for you? Would love to hear what's actually worked, and what's failed.

I've been running a Voice AI agency with just my co-founder for a while now and one thing that keeps coming up is how to build a client fulfillment and delivery process that doesn't break when we scale. I've tried setting up basic automations and project boards, which helped a bit but still leaves us doing too much manual admin and back-and-forth communication. Also tried standardizing our initial onboarding, but it doesn't solve the project management bottlenecks that happen during the actual delivery phase.

Curious how others here handle this , is there a better system or tool or habit that's worked for you? Would love to hear what's actually worked, and what's failed.

What's up everyone? I'm building custom voice AI receptionists.

Are you doing this at scale? Deploying your voice AI systems directly into client ops? If so:

• What deployment methods are you using?
  • SaaS embeds (e.g., via Twilio, custom APIs on their sites)?
  • On-prem
  • Cloud-hosted (AWS Lambda, Vercel) with telephony hooks (SIP/WebRTC)?
  • Hybrid-e.g., make.com/Framer for workflows + voice agen
• How do you integrate seamlessly? Client CRMs (HubSpot, Salesforce), calendars (Google/Outlook), or custom dashboards?
• Data privacy-how are you locking it down?
  • Self-hosted servers (e.g., hMailServer, on-prem DBs)?
  • Encryption (end-to-end for calls/transcripts), GDPR/HIPAA compliance?
  • Client data isolation-separate tenants, no-log policies, or audit logs?
  • Any wild stories of breaches or compliance headaches?

For context, I'm eyeing Indian clients, also figuring out how to create a pricing plan for that as well. Would love to hear from how you guys are approaching this.

I've been doing outreach on LinkedIn for a while now and I genuinely can't tell anymore if I'm the problem or if this is just how it is for everyone.

Every day it's the same mess:

• How many DMs did I actually send this week?
• Who needs a follow-up and when?
• Wait, did I already follow up with this person?
• Who am I currently in a real conversation with vs. who ghosted me?
• Who needs 2nd follow up? who needs 3rd?

LinkedIn's native inbox is honestly useless for any of this. Search is broken half the time, there's no way to tag people, no proper status tracking, no follow-up reminders. I've tried dumping everything into a spreadsheet but I always fall behind updating it, and then I'm back to square one scrolling through my inbox trying to remember who's who.

I'm starting to spend more time managing the conversations than actually having them.

So genuine question - am I the only one struggling with this? How are you all handling it? Notion? Some CRM? A VA? Or are you just vibing and accepting the chaos like I apparently was?

Would love to hear what's actually working for everyone.

What Sofia does

• Picks up inbound calls when staff can't
• Takes reservations and modifies/cancels existing ones
• Handles takeout and delivery orders
• Answers menu, hours, and location questions
• Allergen handling with hard guardrails (transfers to human if unsure)
• Validates delivery addresses against the restaurant's zone
• Bilingual Spanish/English with mid-call language switching
• Logs every call into a dashboard the owner reviews

Stack

• LiveKit - realtime voice layer (migrated from Bolna)
• GPT-4o-mini - reasoning model; cost/latency beat larger models for this use case
• Supabase (Postgres + Edge Functions) - state, menus, reservations, call logs
• Railway - agent infra hosting
• Cartociudad + Google Maps + GPT-4o-mini - three-stage delivery address validation
• V0/Vercel - owner-facing CRM dashboard

What broke and what fixed it

Latency. Bolna was fine for prototyping but hit a ceiling. Migrating to LiveKit gave us finer control over turn detection and barge-in. Painful migration, worth it.

Address validation was harder than the entire reservation flow. Spanish addresses are messy and Google Maps returns confidently wrong results. Ended up with Cartociudad for canonical data, Google Maps for geocoding, and GPT-4o-mini as a disambiguation layer when they disagree.

Allergens Ingredient data lives in structured Supabase tables, not in the prompt. The agent reads from the table - it doesn't reason about ingredients it wasn't given. Low confidence or out-of-scope questions trigger a human transfer. Better to hand off than hallucinate.

Menu drift. Chef changes specials, items go off mid-week. The owner now updates menu and hours from the dashboard; the agent reads live state on every call.

Bilingual switching. Detecting language at the utterance level instead of the call level was the unlock. Callers switch Spanish-English mid-sentence and humans handle it without thinking - agents fumble it by default.

What I'd do differently

• Start on LiveKit, skip the Bolna detour
• Build address validation before the reservation flow
• Never hard-code anything that changes weekly