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A US car dealership was answering every shopper inquiry by hand. I built an AI assistant that talks to shoppers, searches live inventory, and brings in the sales team only when someone is ready to buy.
How it works:
A conversation agent keeps the context of the chat
An inventory lookup finds the matching cars
The AI compares each one against what the shopper asked for
Built with n8n and OpenAI
Result: the manual inquiry process is gone, and sales only talks to qualified buyers.
Need an AI assistant or automation for your business? My services are on my profile.
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Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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I built an AI voice ordering workflow to help a restaurant capture customer orders and pass them to the kitchen with less manual work.
Using Vapi, I configured a voice assistant with the restaurant’s menu and prices to collect customer details and orders. After each call, a webhook triggers an n8n workflow, where OpenAI extracts the order into structured data. The workflow then notifies the kitchen and logs the order in Google Sheets.
I handled the voice assistant setup, webhook integration, AI prompts, and workflow implementation. The solution reduced manual order entry and made order information easier for the kitchen to access.
Tools: Vapi, n8n, OpenAI, Google Sheets, and webhooks.
Having the assistant feed orders straight into the kitchen cuts the manual handoff. The call transcript in Sheets also gives a clear audit trail.
Automated LinkedIn Hiring Signal & AI Outbound Engine
Overview:
Designed and deployed an autonomous outbound lead generation system using n8n. The workflow captures hiring intent signals from LinkedIn, identifies relevant executive buyers, enriches verified contact data, and drafts contextualized sales copy through an integrated LLM.
Tech Stack:
n8n • Apify • SearchLeads API • OpenRouter (Nemotron LLM) • Google Sheets API • Telegram Bot API • JavaScript
Core Deliverables:
Automated Signal Scraping: Continuous monitoring of fresh job posts across target industries.
Granular Data Filtering: Exclusion logic for staffing agencies, company headcounts over 250, and unverified domains.
Multi-Source Enrichment: Automated discovery of decision-makers (C-Level, VP, Director) with validated work emails.
Context-Aware Email Generation: Custom prompting architecture that maps the open role's requirements directly into a tailored value proposition.
Data Synchronization & Alerts: Bi-directional sync with Google Sheets and real-time push alerts via Telegram.
Impact:
Replaces 10+ hours of weekly manual SDR prospecting with a continuous background process that delivers high-intent, enriched leads directly to the sales inbox.
Testing my app! 🧰🚀 Everything is finally coming along.
I’ve been working on this project for a little over two weeks. Initially it was just me working with one AI agent, but I was still manually coding most of it, so I was moving like a turtle 🐢very slow.
Then I decided to implement Codex into my project to automate more of the development and it has been amazing. Now I can focus more on prompting, testing, reviewing the code and making the technical decisions instead of manually coding everything.
I also created my own AGENTS.md bible with all my project rules and instructions to make sure Codex follows them as the final authority when working on my code.
The idea is simple: create one useful and intuitive ecosystem of tools that Shopify merchants can add to their stores to help customers make purchasing decisions faster and with more confidence.
Still testing, building and adding more tools. Let’s see where this goes! 🚀
And if anyone finds the idea interesting. I’m definitely open to collaborations, ideas or partnerships. Feel free to reach out!
Seeing you shift from hand coding to Codex and let the agent handle the grunt work really speeds up iteration.