Quick Overview This workflow runs daily to review Japanese ad copy in Google Sheets using Google Gemini, writes compliance risk results back to the sheet, and alerts the right team in Slack (and drafts a Gmail revision request) based on high/medium/low risk. How it works Runs every day at 9:00 on a schedule. Reads ad copy rows from Google Sheets to find items that still need a compliance check. Sends each copy item to Google Gemini with the configured product category, target laws, and extra rules to generate a risk level, violations, and a compliant rewrite. Parses and normalizes the Gemini output into fields like risk level, violation count, and safe rewrite, and posts a Slack alert if the AI check fails. Updates the corresponding Google Sheets row with the compliance results to keep a record of the review. Routes the item by risk level and posts to Slack for legal blocking (high), marketing review (medium), publish-ready notification (low), or manual review when the result is inconclusive. For high-risk copy, also creates a Gmail draft requesting the author to revise the copy using the suggested compliant rewrite.
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GmailGoogle Gemini Chat Model
Google SheetsSlackRelated workflows
See all AI Automation→Send and track Slack invoice requests with Gemini, Google Sheets and Gmail
Quick overview Youtube Video: https://youtu.be/42-oHh9w9Eo This workflow listens for Slack @mentions, uses Google Gemini to classify the request and extract invoice details, then reads and updates Google Sheets, generates invoice PDFs with PdfBro, sends invoices or reminders via Gmail, and posts confirmations or errors back to Slack. How it works Triggers when the workflow’s Slack app is mentioned in a specified Slack channel. Uses Google Gemini to classify the message intent (send invoice, remind invoice, or check status) and extract the recipient email and invoice due date. Routes the request based on the extracted intent and stops if the intent cannot be determined. For SEND_INVOICE, looks up the client in a Google Sheets “Client Bill” spreadsheet and posts a Slack error if no matching email is found. If a client is found, generates an invoice PDF with PdfBro, emails it to the client via Gmail, appends/updates the invoice record in a Google Sheets “Client Invoices” spreadsheet, and posts a Slack confirmation. For REMIND_INVOICE, finds an UNPAID invoice for the email in the “Client Invoices” Google Sheet, regenerates the invoice PDF with PdfBro, emails a reminder via Gmail, and p
Draft personalized cold emails from Google Sheets using Gemini and HubSpot
Quick overview This workflow batch-processes leads from Google Sheets, researches each person and company using Tavily plus Google Gemini, drafts a personalized cold email, then creates/updates the contact in HubSpot with a research note and a saved email draft before marking the lead as Done in the sheet. How it works Runs manually and sets a batch size that controls how many leads to process per run. Reads leads from Google Sheets, skips rows already marked as Done, and normalizes the selected batch into clean lead fields. Processes the batch one lead at a time and uses Tavily search (last 60 days) with Google Gemini to extract the most recent public activity, pain points, and a personalization hook. Cleans and parses the research JSON so it can be reused reliably downstream. Uses Google Gemini to draft a 90–120 word cold outreach email (subject and body) that incorporates the research and offers a free “Automated LinkedIn Post Creator” n8n workflow. Creates or reuses the HubSpot contact, logs a HubSpot note with the research and drafted email, and saves the email as a HubSpot engagement in DRAFT status. Updates the matching row in Google Sheets (by Email) to set Status to “Done
Generate weekly student progress reports with Gemini, Supabase, and WhatsApp
Quick overview This workflow runs weekly to pull student attendance and score data from Supabase, uses Google Gemini to generate per-student performance summaries and attention flags, sends immediate WhatsApp alerts for flagged students, then compiles all summaries into a PDF report, uploads it, and shares it with the coach via WhatsApp. How it works Runs weekly on a schedule. Fetches all student weekly metrics (attendance and scores) from Supabase. Uses Google Gemini to write a short performance summary per student and determine whether the student should be flagged for attention based on attendance and score-drop rules. If a student is flagged, sends a WhatsApp message to the coach and inserts a flag record into Supabase. Aggregates all students’ summaries into a single HTML weekly report. Converts the HTML report to a PDF via an HTTP-based HTML-to-PDF API, uploads the PDF to a file-hosting API, and sends the PDF link/document to the coach via WhatsApp. Logs the report URL to Supabase for recordkeeping. Setup Add Supabase credentials and create the required tables/columns (weekly_student_data, attention_flags, and weekly_reports) referenced by the workflow. Add a Google Gemini (P