Estimate Construction Costs from Revit/IFC Models with GPT-4 and Claude

Customer personality (BaZi, DISC, Numerology) with Gemini & Google Sheets

What this workflow does This workflow turns your n8n into an automated personality-insights engine driven by Google Sheets. When a row is updated with Analysis Status = Run, it: - Computes Lunar Date of Birth and Four Pillars (BaZi) from DOB and optional birth time. - Calculates Numerology (Life Path, Birth Day, Pinnacles/Challenges, Expression, Soul Urge, Personality, Maturity) and a phone “vibration” number. - Generates concise, sales-oriented bullet-point analyses with Gemini for BaZi, Numer

Email summary agent

Problem Teams often struggle with email overload, leading to missed actions and inefficient meeting preparation. Solution This workflow automates email management using n8n and AI. It fetches emails, summarizes key points and actions, and sends two concise updates—one in the morning and one at night. How It Works - Triggers at 7 AM and 9 PM: Automates the process to summarize emails received during specific time blocks. - Fetches Emails: Retrieves emails from the last 24 hours or af

AI Timesheet Generator with Gmail, Calendar & GitHub to Google Sheets

AI-Powered Automatic Timesheet Generator for Google Sheets Stop wasting billable hours on manual time-tracking. AutoTimesheet Pro uses AI to collect emails, meetings, and GitHub work, then writes a clean timesheet straight into Google Sheets. Perfect for developers, consultants, agencies, and remote teams. Get Started with n8n now! --- 🚀 Key Features - Automated Google Sheets time-tracking — zero spreadsheet prep. - AI-generate

Get blockchain insights from chat using GPT-4 and Nansen MCP

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow listens for an incoming chat message and routes it to an AI Agent. The agent is powered by your preferred Chat Model (such as OpenAI or Anthropic) and extended with the Nansen MCP tool, which enables it to retrieve onchain wallet data, token movements, and address-level insights in real time. The Nansen MCP tool uses HTTP Streamable transport and requires API Key authen

Content farming - : AI-powered blog automation for WordPress

Upgrade to V4== We’ve released Version 4 of our AI Powered Blog Automation workflow. We heard your complains and made a complete redesign built for serious content creators. ChatGPT 5, Inbound Links, Verified Outbound Links,YOAST seo integration, Company profile, higher SEO ranking, banner images using companys mascot, FAQ sections and conclusions, 35% cost reduction, 📝 Read the New Articles published by Content Farming v4 🛒 View the updated and improved v4 workflow 👻 No technical experience ?

AI content creation and publishing engine with Mistral, Creatomate, and YouTube

Description This n8n workflow automates the entire process of creating and publishing AI-generated videos, triggered by a simple message from a Telegram bot (YTAdmin). It transforms a text prompt into a structured video with scenes, visuals, and voiceover, stores assets in MongoDB, renders the final output using Creatomate, and uploads the video to YouTube. Throughout the process, YTAdmin receives real-time updates on the workflow’s progress. This is ideal for content creators, marketers, or bus

Automatically save & organize LINE message files in Google Drive with Sheets logging

Overview This workflow automatically saves files received via LINE Messaging API into Google Drive and logs the file details into a Google Sheet. It checks the file type against allowed types, organizes files into date-based folders and (optionally) file type–specific subfolders, and sends a reply message back to the LINE user with the file URL or an error message if the file type is not permitted. Who is this for? Developers & IT Administrators: Looking to integrate LINE with Google Drive and S

Evaluate RAG response accuracy with OpenAI: document groundedness metric

This n8n template demonstrates how to calculate the evaluation metric "RAG document groundedness" which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents. The scoring approach is adapted from How it works This evaluation works best for an agent that requires document retrieval from a vector store or similar source. For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to as