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Zero pending follow‑ups and a 62% closing rate sounded impossible until I built an AI voice agent for follow‑up reminder calls.
The problem was clear: four companies were losing deals because sales reps never got back to prospects on time.
I wired n8n with Vapi to create a hands‑free voice agent that called leads, logged responses, and nudged reps only when needed.
Within weeks the pipeline cleared – no pending follow‑ups and the closing rate jumped to 62%.
The key lesson for freelancers and founders: automate the repetitive outreach steps, but keep the human hand in the loop for the final push.
The blend of low‑code workflow and AI voice saved hours and lifted revenue without extra headcount.
What part of your sales process could benefit from a similar AI‑driven reminder system?
The nudge only when needed part is the smart bit here. Full automation on follow-ups usually scares people off, but an agent that clears the routine calls and only pulls the rep in for the final push keeps the human trust intact.
How did you decide which calls the agent should...
Thanks, Muhammad. Straight answer: the agent never handles a prospect call on its own. It calls the reps, not the leads. Each rep gets a call with the follow-ups due and the next task on every lead, so nothing sits forgotten. Every prospect conversation stays with a human. So...
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Building a Voice AI Assistant That Turns Phone Calls Into Thoughtful Follow‑Through
I built a Django backend for a family-focused AI phone assistant. A registered caller connects through Twilio, and Django Channels streams the call to an OpenAI Realtime session for a natural, two-way conversation.
The backend adds caller-specific context, selected voices, subscription minute limits, and interruption handling. After the call, background tasks generate a separate summary. A follow-up email is sent only when requested and the recipient is confirmed.
I also built APIs for managing relations, subscriptions, and dashboard usage data. One of the most interesting parts was connecting the whole lifecycle: incoming call, real-time conversation, usage tracking, and post-call follow-through.
#Django #VoiceAI #RealtimeAI #Twilio #OpenAI #BackendDevelopment
Most small businesses lose clients in the gap between "new request" and "someone replies".
This year I shipped 5 projects that close that gap.
→ n8n AI agents that score every lead and reply with a personalised email in seconds
→ MedAssist AI, a SaaS that lets patients book and get answers 24/7
→ Kaizen Kyoto Capital, a crypto SaaS live with Paddle billing, 2FA and 43 automated tests
→ Two premium redesigns (luxury real estate in 3D, a cosmetics brand) with before/after
I'm a full-stack & AI automation developer, available now for websites, SaaS MVPs and n8n automations. French, English, Arabic. I reply within 24h.
Got a process that eats your team's time? Send me a message and I'll map your first automation for free.
Good work, keep going
Black Box: a flight recorder for AI phone calls.
AI receptionists take thousands of calls, and every one deserves a black box. Black Box is a Video.js v10 skin for reviewing call recordings, styled as a hi-vis flight recorder. The seek bar is the tape: a two-lane waveform with the AI agent above the line and the caller below, so you can see who spoke before you press play. Hover anywhere to read that line. Flags mark the moments that matter (connected, booked, objection, closed), and the level meters, REC lamp, captions and transcript all run off real player state. It is keyboard-first, readable over bright and dark footage (try the test bench above the player), works from 360px up, and calms down under reduced motion.
a flight recorder for ai phone calls is such a clever use case, black box feels like a real product