Tags: Supply Chain, Logistics, AI Agents Context Hey! Iām Samir, a Supply Chain Data Scientist from Paris, and the founder of LogiGreen Consulting. We design tools to help companies improve their logistics processes using data analytics, AI, and automationāto reduce costs and minimize environmental impacts. >Letās use N8N to improve logistics operations! š¬ For business inquiries, you can add me on LinkedIn Who is this template for? This workflow template is designed for logistics or manufacturing operations that receive orders by email. The example above illustrate the challenge we want to tackle using an AI Agent to parse the information and load them in a Google sheet. If you want to understand how I built this workflow, check my detailed tutorial: š„ Step-by-Step Tutorial How does it work? The workflow is connected to a Gmail Trigger to open all the emails that include Inbound Order in their subject. The email is parsed by an AI Agent equipped with OpenAI's GPT to collect all the information. The results are pulled in a Google Sheet. These orderlines can then be transferred to warehouse teams to prepare *order receiving. What do I need to get started?
Tags
Google Sheets
OpenAI Chat Model
Structured Output ParserRelated workflows
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AI: Summarize podcast episode and enhance using Wikipedia
The workflow automates the process of creating a summarized and enriched podcast digest, which is then sent via email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
Monitor overtime risk against Japanese labour caps with Gemini, Sheets, Slack & Gmail
Quick Overview This workflow runs weekly to read attendance overtime from Google Sheets, totals it per employee and month, uses Google Gemini to classify risk against Japanese labour-law limits, writes results back to Sheets, and escalates high-risk cases via Slack and a Gmail draft. How it works Runs every week on a schedule. Loads configured Japanese overtime limits and fetches raw attendance rows from a Google Sheets āAttendanceā worksheet. Aggregates overtime hours per employee per month. Sends each employee-month total to Google Gemini, which returns a structured risk level (over/approaching/ok) plus a short summary and recommended manager actions. Stores or updates the assessment in a Google Sheets āOvertime Statusā worksheet keyed by employee and month. Posts to Slack when overtime is over the cap (and drafts a manager notice in Gmail), posts an early-warning Slack message when approaching the cap, and flags unclear or failed assessments to Slack for manual review. Setup Add credentials for Google Sheets OAuth, Google Gemini (PaLM) API, Slack OAuth2, and Gmail OAuth2. Create a Google Sheets spreadsheet with an āAttendanceā sheet containing Employee (or Name), Month (or Date)
Monitor Japanese business partners for registry changes with gBizINFO and Gemini
Quick Overview This workflow runs weekly to check Japanese business partners listed in Google Sheets against the gBizINFO corporate registry API, uses Google Gemini to assess the risk impact of detected changes, updates the stored partner snapshot, and escalates findings to Slack and Gmail based on materiality. How it works Runs every week on a schedule. Reads the partner list (including corporate numbers and last-known name/address) from Google Sheets. Queries the gBizINFO corporate registry API for each partner and posts a Slack message if the lookup fails. Compares the latest registry data to the stored snapshot to detect name, address, or closure/dissolution changes and continues only when changes are found. Sends the detected changes to Google Gemini to classify materiality (high/medium/low) with a short summary and recommended action, and posts a Slack message if the assessment fails. Updates the Google Sheets partner snapshot with the latest registry details so the change is recorded. Routes by materiality to notify Slack (medium/other), and for high materiality also posts a Slack alert and creates a Gmail draft requesting a credit review. Setup Create a Google Sheets spread