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This project solves a common small-business pain point: inventory running out silently because no one's watching stock levels in real time.
Trigger 1 — Order processing: A webhook receives new orders (supporting multiple items per order). Each item is split out individually, matched to its corresponding row in a Google Sheets inventory log by SKU, and the stock count is automatically decremented — with the "Last Updated" timestamp refreshed on every change.
Trigger 2 — Daily stock monitoring: A scheduled trigger runs once a day, scans the entire inventory sheet, and checks every item's current stock against its own custom reorder threshold. Any item running low automatically triggers a Slack alert listing the item name, SKU, current stock, and threshold — so restocking decisions happen before a customer ever notices a shortage.
I'd test two orders hitting the same SKU at once, since both can read the same stock count before either writes back to Sheets. Are you serializing stock updates per SKU, or using another way to prevent a lost decrement?
Good catch — you're right that two simultaneous orders for the same SKU could cause a lost update under the original design (read-then-write race condition).
I've since reworked the stock logic: instead of directly overwriting the stock count, new orders now get appended to a...
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AI-Powered Email Classification Workflow | n8n Automation
Built an intelligent email automation system using n8n that automatically reads incoming emails, classifies them by department using AI, and forwards them to the right team without any human input.
The workflow connects directly to Gmail and triggers the moment a new email arrives. A JavaScript node extracts the key email details, including sender, subject, body, and date, before passing them to an AI Agent powered by GPT-4o-mini. The AI reads the email content and classifies it into one of six departments: Sales, Customer Service, HR, Finance, Operations, or Other.
A Switch node then routes the email down the correct branch, and a Gmail node automatically forwards it to the right department inbox with a clear label in the subject line.
What it does:
Monitors a Gmail inbox in real time
Extracts and cleans email data automatically
Uses AI to classify emails by department
Routes and forwards emails to the correct team
Fully automated with zero manual sorting required
Result:
Emails that would normally sit unread or require manual sorting now reach the right department within seconds of arriving.
Nice implementation. The production question is what happens to ambiguous emails. I usually add a confidence threshold, an “unclassified” review queue, and retention of the original message so a routing mistake can be corrected without losing context.
Top-notch design.
Designed and built an AI operations dashboard that brings projects, decisions, tasks, research, connected tools, and voice interaction into one clear workspace. The goal is to turn complex workflows into a simple, usable system that helps people see what matters and act faster.
James, putting decisions right next to tasks is the part I like most. Most ops tools track what got done but lose why it was decided, and that is exactly what people go looking for three weeks later. How are you using the voice side day to day?