The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Built an AI voice agent that books real gym classes live, over a call.
No app, no form. You call, say what you want, and the agent checks availability, books the slot, and confirms it back to you all in real time.
Stack: Vapi (voice) + n8n (backend logic) + Airtable (data layer)
The clip below shows the automation firing in real time as the call happens: availability check → booking created → confirmation sent back to the caller.
Building this out as a portfolio piece for AI voice agent work — open to building something similar for your business.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Built this AI agent to find, organize, and manage leads through Gmail, helping automate lead handling and outreach.
n8n is absolute gold for orchestrating lead pipelines like this! Connecting Gmail parsing with LLM qualification saves teams dozens of hours weekly. As someone who builds custom agentic lead automation workflows, seeing clean visual architectures like this is super satisfying. Top-tier build, Talha!.
I built Aurora, a booking experience for Studio Aurora Beauty, a fictional solo beauty studio in Belo Horizonte, Brazil.
The problem was simple: the owner was spending too much time answering availability questions, confirming appointments, sending reminders and handling rescheduling through WhatsApp and Instagram.
Aurora turns that manual back-and-forth into a seamless booking flow.
Customers can choose a service, check real-time availability, book an appointment, receive instant confirmation, and reschedule or cancel without contacting the owner.
On the business side, the owner gets a dashboard with upcoming appointments, booking statuses, pending confirmations and automated reminders.
The goal was not to build another calendar. It was to reduce the manual work around booking.
From “Can I book with you?” to “You’re booked.”
Another late night. Building a quant trading system an agentic model where different AI agents handle research, testing and risk, and none of them is allowed to place a trade on its own.
The hardest part so far? Being honest when the results say "not yet." Most strategies I've tested failed once real costs were included. That's exactly what testing is for.
Keeping The Psychology of Money and The Diary of a CEO close while I figure it out. What are you reading these days?
Curious how you’ve separated the agents from execution. When you say none can place a trade on its own, is that enforced through a separate execution service with fixed risk checks, human approval or both? I’d love to understand where the agent's decision-making ends and the hard rules take over.