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4 contributions to Brendan's AI Community
How I built an end-to-end AI Voice Receptionist that actually books appointments (Vapi + Retell + n8n Architecture Breakdown)
How I Built an AI Voice Receptionist That Actually Books Appointments (Under 800ms Latency) Hey everyone! 👋 70%+ of after-hours callers hang up the second they hear a voicemail beep—and book with the next competitor on Google. Alongside our platform work at Oqvera, I’m expanding my custom voice AI and automation services to Fiverr. Here is the exact production blueprint I use to automate inbound calls and eliminate missed leads: 🛠️ The Core Stack - Voice & Telephony: Vapi AI / Retell AI + Twilio - STT & Audio: Deepgram Nova-2 + Cartesia / ElevenLabs - LLM Engine: GPT-4o / Claude 3.5 Sonnet (Tool Calling) - Automation & CRM: n8n / Make.com + GoHighLevel / Cal.com ⚙️ How the System Operates 1. Sub-800ms Inbound Response: Instant, human-like voice handling with zero awkward robotic pauses. 2. Dynamic Live Scheduling: AI queries live calendar slots via API in real time, avoids double bookings, and reserves appointments on the spot. 3. Guardrailed FAQs: Answers pricing, location, and service questions with zero hallucinations. 4. Automated Post-Call Sync: n8n instantly pushes call transcripts to CRM, fires an SMS confirmation to the caller, and initiates warm transfers for emergency cases. 💡 Pro Tip Keep total round-trip latency under 1 second and always set up an SMS/transfer fallback for edge cases. If you want a ready-to-deploy voice receptionist for your business or clients: 👉 Check out my Fiverr Gig: https://www.fiverr.com/s/AGBz4qX For the voice builders here: Vapi or Retell AI—what is your go-to framework right now? Let’s talk below!
How I built an end-to-end AI Voice Receptionist that actually books appointments (Vapi + Retell + n8n Architecture Breakdown)
1 like • 3d
@James Bradford Thanks bro! Yeah, I’m excited to see how it translates to Fiverr too. I’ll keep you posted on how it goes 🤝
0 likes • 3d
@Mouldi Nouri 100% bro. That human handoff is definitely one of the most important parts. The AI should know its limits and bring in a human when needed rather than trying to handle everything. Keeping the system simple and reliable is the goal 🤝
I’m officially launching OQVERA 🚀 — and I built it to put my work where people can actually see it.
Hey everyone 👋 I’m Saad, an AI/ML Engineer and developer, and today I’m excited to introduce something I’ve been building: OQVERA. I didn’t want to create another website that simply says: “We build AI solutions.” I wanted to build something that shows what I can actually build. So OQVERA is becoming my public engineering portfolio — a place where I showcase real projects, AI systems, automation workflows, agentic applications, and the technical work behind them. What you’ll find inside OQVERA 👇 🤖 AI & Agentic Systems Multi-agent architectures, AI agents, RAG systems, LangGraph workflows, intelligent assistants, and LLM-powered applications. ⚙️ Automation & Workflows Business process automation, API integrations, AI-powered workflows, calling agents, and systems designed to remove repetitive manual work. 💻 AI Engineering & Software Backend systems, APIs, AI integrations, computer vision, intelligent applications, and production-focused engineering. 🔬 Case Studies I’m documenting projects not just by showing the final UI, but by explaining the problem → architecture → technology → implementation → outcome. Why I built OQVERA I want my work to speak for itself. Instead of telling potential clients: “I can build an AI agent.” I can show them one. Instead of saying: “I know automation.” I can show the workflow. Instead of listing 20 technologies on a CV... I can show what I built with them. That’s the direction I want to take with OQVERA. And yes — I’m building this with clients in mind. If you're a founder, business owner, startup, or team looking at ways to use: - AI agents - LLMs - workflow automation - intelligent customer support - AI calling systems - RAG / knowledge systems - custom AI software - internal business automation I'd love for you to check out what I'm building. 🌐 OQVERA: https://oqvera.netlify.app/ This is only the beginning. I’ll be continuously adding new projects, experiments, architectures, and case studies as I build.
0 likes • 9d
@Mouldi Nouri okay. Your feedback is very precious for me Thank you
0 likes • 4d
@Kelly Lynch 100% agree. The "messy middle"—navigating architectural trade-offs, edge cases, and cost constraints—is where real engineering happens. That’s exactly what I'm highlighting in these breakdowns. Thanks for the insight!
How I Built a 24/7 AI Voice Receptionist Using Vapi, Make.com, & Google Sheets (Full Setup) 🚗 Voice AI Automation
Hey everyone! 👋 ​I wanted to share a complete real-world Voice AI build I just wrapped up: Alex, an automated AI Voice Operations Receptionist for a pre-owned auto dealership (National Motors Inc.). ​If you’re building voice agents for local businesses, lead generation, or appointment setting, here is how the whole stack works under the hood. ​🔥 What the Voice Agent Handles Live on Calls: ​Real-time Inventory Lookups: Queries the live inventory database (make, model, mileage, pricing, stock numbers) and answers caller questions instantly. ​Test Drive Booking: Captures caller details (Name, Phone, Email, Preferred Date/Time) and logs them directly to a Google Sheet. ​Instant Email Confirmations: Automatically triggers HTML booking confirmation emails via Gmail right after hanging up. ​Trade-in & Financing Routing: Collects trade-in specs and guides callers through pre-qualification flows. ​🛠️ The Tech Stack: ​Vapi.ai: Voice Engine (STT/TTS/LLM orchestration with custom system prompts). ​Make.com: Central Webhook Router handling function tool execution. ​Google Sheets: Functioning as both a live database for dynamic lookups and a CRM lead sheet. ​Gmail API: Instant email confirmations. ​⚡ Key Takeaways & Common Pitfalls to Avoid: ​If you’re trying to build something similar in Vapi + Make.com, keep these technical details in mind: ​Array Indexing Matters: Vapi passes tool calls as a nested array (toolCalls[1]). If you map fields as toolCalls[] inside Make.com, your JSON strings will break, resulting in "No result returned" timeout errors! ​Routing Function Calls: Always set explicit Filter Rules directly on your Make.com Router modules (e.g., function.name EQUALS book_test_drive) so different tool execution branches don't trigger at the same time. ​Return Clean Webhook Responses: Always return an explicit 200 OK status with Content-Type: application/json header and a results array containing the toolCallId. Otherwise, the AI assistant will time out waiting for backend confirmation!
1 like • 29d
@Brendan Jowett Great point. Logging the transcript snippet alongside the "toolCallId" makes debugging much more actionable. It helps distinguish prompt/agent issues from downstream automation failures and creates a solid feedback loop for improving the system. Thanks for the insight!
🚀 AI Engineer | Looking for Serious Collaborators
Hey everyone! I'm Muhammad Saad, an AI Engineer focused on building production-ready AI solutions. My expertise includes: • AI Agents & Multi-Agent Systems • LangGraph & CrewAI • RAG (Retrieval-Augmented Generation) • LLM Applications • AI Chatbots & Voice AI • Workflow Automation • FastAPI, Python, React & Next.js • API Integrations & Business Automation I've built AI systems for chatbots, automation workflows, research assistants, and custom business solutions. I enjoy taking ideas from concept to deployment. I'm looking to collaborate with founders, marketers, sales professionals, agencies, and other developers who want to build real AI products or start an AI company together. If you can bring ideas, clients, or business expertise, I can handle the technical side and help turn those ideas into reality. If you're serious about building something meaningful, send me a message. Let's create something great together. 🚀
2 likes • Aug 5
@Okasha Khan Thank you, Okasha! I really appreciate the kind words and encouragement. Hoping to connect with great people here and build some impactful partnerships. 🤝
1 like • Aug 5
@Malik Ahmed okay. Lets connect and follow
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Saad Mehmood
3
4 points to level up
@saad-mehmood-7912
AI Engineer, working as AI Pipeline Architect, specialized in Agentic Ai and Ai Automtions for business. Founder of OQvera

Active 23h ago
Joined Aug 3, 2026
Pakistan
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