Quick overview This workflow runs daily or via an on-demand webhook to pull financial metrics, operational KPIs, and market quotes via HTTP APIs, then uses OpenAI to detect anomalies and generate an executive briefing that is POSTed to a dashboard endpoint and logged to Google Sheets. How it works Runs on a daily schedule or receives a POST request via a webhook to start an executive briefing run with a configurable lookback period. Fetches financial metrics, operational KPIs, and market data in parallel from three HTTP API endpoints and continues even if one source fails. Merges and normalizes the three datasets into a single snapshot, marking missing sources as unavailable so downstream steps keep a consistent structure. Uses OpenAI to analyze the snapshot for anomalies, unusual trends, and data gaps, returning a severity-scored findings JSON. Uses OpenAI again to turn the anomaly findings and raw metrics into a structured executive briefing with a health score, risks, opportunities, and recommended actions. Formats a final JSON payload and delivers it by POSTing to your dashboard endpoint and appending a summary row to a Google Sheets tracker.
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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
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.
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