Quick Overview This workflow runs every 15 minutes to pull procurement transactions and department budgets from Google Sheets, calculate spend utilization and forecasts, generate executive risk insights with Groq Llama, write dashboard records back to Google Sheets, and email critical-risk alerts via Gmail. How it works Runs every 15 minutes on a schedule. Reads procurement transactions and department budget/threshold data from Google Sheets and combines them by department. Aggregates spend per department, calculates utilization, remaining budget, projected monthly spend, vendor counts, pending transactions, and assigns SAFE/WARNING/CRITICAL risk levels. Uses Groq (Llama 3.1) to generate an executive-friendly risk analysis and recommendations for each department based on the calculated metrics. Builds organization-wide dashboard totals (spend, projections, alert counts, highest-spend and top-risk departments) and attaches workflow metadata. Formats the results into executive summary, department insight, and risk alert records and appends them into separate Google Sheets tabs. Sends a Gmail escalation email when a CRITICAL risk alert record is detected.
Tags
Gmail
Google Sheets
Groq Chat ModelRelated workflows
See all AI Automation→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.
Route WhatsApp support requests with Claude, Supabase, HubSpot and Slack
Quick overview This workflow turns incoming WhatsApp messages (text, audio, images, and documents) into actionable support interactions by extracting content, detecting sentiment, and using an AI agent with a Supabase knowledge base to route requests to Google Calendar, HubSpot, Slack, Gmail, and back to WhatsApp. How it works Receives incoming WhatsApp messages via a WhatsApp webhook trigger. Routes the message by type and converts it into text using OpenAI Whisper for audio, OpenAI GPT-4o Vision for images, or a PDF extractor for documents (or passes text messages through). Loads the sender’s session context from Supabase and runs sentiment/language detection on the extracted text. Uses a LangChain AI agent (Claude) with Supabase vector search (with OpenAI embeddings and Cohere reranking) plus tool access (Google Calendar, HubSpot, Slack, and Gmail) to produce a structured intent, response, and metadata. Logs conversation analytics (intent, sentiment, message type, and response length) to an n8n Data Table. Routes by intent to either create a Google Calendar event, create/update a HubSpot contact, email a document via Gmail (and upload it to Google Drive), create a HubSpot ticket
Create TikTok carousel posts with Upload Post, Google Sheets, Gemini, GPT-4.1
Quick overview This workflow runs daily to pull TikTok post and profile analytics from Upload Post, updates a Google Sheets performance log, uses Google Gemini and OpenAI to generate a new carousel concept and caption, creates four images via fal.ai, publishes to TikTok, and updates a persistent “Agent Skill” sheet. How it works Runs on a daily schedule (or manually) and loads product, Upload Post, and Google Sheets configuration values. Reads the Google Sheets “Performance Log,” selects posts missing stats or posted recently, fetches TikTok post analytics from the Upload Post API, and writes updated metrics back to the sheet. Aggregates the refreshed history, fetches TikTok profile analytics from Upload Post, reads the “Agent Skill” sheet, and compiles a single context summary. Uses Google Gemini (via a structured JSON output) to generate a TikTok carousel plan including caption, strategy notes, four slide prompts, hashtags, and an engagement question. Sends the four prompts to fal.ai to generate four 9:16 PNG carousel images and collects their hosted image URLs. Uses OpenAI (GPT-4.1) to write a short TikTok photo-post description, publishes the carousel to TikTok via Upload Post