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I Build AI Voice Agents That Answer Calls & Book Meetings — Like a Human
No more missed calls.
VAPI + n8n + GoHighLevel + Calendar + CRM
How my Voice Agent works:
Customer calls your business
AI answers in <2 sec — natural human voice (English/Bangla/Spanish)
Understands intent — support / booking / sales
Checks real availability in Google Calendar
Books meeting + sends SMS confirmation
Updates GHL CRM + triggers follow-up
Use cases:
Dental / Clinic / Salon — auto book appointments
Real Estate — qualify leads + book showings
Ecom — order status + return handling
Agencies — 24/7 lead qualifier
Tech: VAPI AI, n8n, GoHighLevel, Make, Gemini, ElevenLabs
One client saved 15 hrs/week — 47 extra bookings/month.
I setup full system in 3 days.
Want demo call? Comment "VOICE"
#aivoiceagent #vapi #n8n #gohighlevel #aiautomation #voiceai #aichatbot #bookingautomation #elevenlabs #aivoice
The 3 day build timeline works well when the calendar and CRM logic are already mapped out. Most projects stall not on the voice model, but on n8n workflow edge cases during live testing.
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🚀 Just Built an AI Lead Nurturing Agent for B2B Sales Teams!
The problem: Most B2B companies lose leads because follow-ups are slow. By the time a rep reaches out, the lead has already talked to competitors.
The solution: An AI agent that handles the entire lead nurturing workflow:
✅ Scores leads as HOT/WARM/COLD automatically
✅ Sends personalized follow-ups within 60 seconds
✅ Logs everything to Google Sheets/CRM
✅ Alerts reps only for serious buyers
✅ Books meetings directly into calendars
Tech Stack: n8n | OpenAI | Google Sheets | Gmail | Telegram
Result: 60% higher conversion rate, 15+ hours/week saved per rep.
This is like having an AI SDR that never sleeps — for $300/month.
Want this for your sales team? Let's talk.
#AIAutomation #LeadNurturing #B2BSales #SalesOps #n8n #PropTech
The bit about auto booking meetings into calendars looks like it will eliminate a lot of scheduling back and forth.
Your support queue is growing faster than your team can handle.
What if you could resolve 60% of support tickets automatically with AI?
I'm building Relay AI, an AI support agent trained on your docs, tickets, and product. It answers customers in seconds, and escalates to your team only when it should.
Exceptional as always.
This week, I have been working on automating my boss's inbox management, delegating email triage to AI while I handle reviews and approvals that require sound judgment. Because one wrong response to a client can cost a business revenue, I wanted to build a system that saves time without handing over critical decisions to AI.
How I built it:
I created two connected automation scenarios in Make.com.
Scenario 1: Intelligent Inbox Triage:
AI analyzes incoming emails, categorizes them by priority, summarizes their content, and recommends the next action. This makes it easier to identify urgent messages and decide what needs attention first.
Scenario 2: Human Review & Approval:
The workflow supports the review and approval process before an email is sent. Slack notifications help bring relevant updates to my attention, so I can review the proposed action and approve the response before it goes out.
Below are snippets of the two scenarios, including a Slack notification, showing how the workflow operates.
My takeaway? AI can help manage the inbox, but when a response could affect revenue or a client relationship, the final decision should remain human.
I'd test the triage with urgent emails that sound casual, such as 'I still can't access the account.' Do you review a sample of low-priority messages to catch urgent ones the AI missed?