Send personalized WhatsApp templates triggered by KlickTipp with auto-responses

Automatic travel itinerary generation via email with Llama AI

Travel Agent that Auto Response on Mail In this guide, we’ll break down how to set up an AI-powered auto-reply system that works while you sleep. Ready to 10X your efficiency? Let’s dive in! What’s the Goal? - AI-driven auto-responses for Email. - Instant replies to FAQs, order confirmations, and support queries. - 24/7 availability - no more “We’ll get back to you soon” delays. - Seamless integration with existing business tools. By the end, you’ll have a self-running communication assistan

Detect Dialogflow intents for new WhatsApp messages

Every time a new message is received on WhatsApp, Make will automatically detect the intent with Google Dialogflow API. Then, the intent's output is sent as a reply in WhatsApp.

AI-powered WhatsApp customer support for Shopify brands with LLM agents

AI-Powered WhatsApp Customer Support for Shopify Brands This n8n template builds a WhatsApp support copilot that answers order status and product availability from Shopify using LLM "agents," then replies to the customer in WhatsApp or routes to human support. ------------------------------------------------------------------------ Use cases - "Where is my order?" → live status + tracking link - "What are your best-selling T-shirts?" → in-stock sizes & variants - Greetings / small talk → welcome

AI email assistant: Prioritize Gmail with ChatGPT summaries and Slack digests

This n8n workflow acts as an AI-powered Inbox Assistant that automatically summarizes and classifies Gmail emails, prioritizes important messages, and sends a daily digest to Slack. It’s ideal for startup founders and small teams juggling investor intros, customer leads, and support queries — all from a busy Gmail inbox. Each email is processed using ChatGPT to generate a concise summary, classify the message (e.g., Support, Investor, Spam), and determine its urgency. High and medium priority m

AI-powered multi-platform assistant with Google Suite, LinkedIn & Twitter

MCP Personal Assistant Workflow Description This workflow integrates multiple productivity tools into a single AI-powered assistant using n8n, acting as a centralized control hub to receive and execute tasks across Google Calendar, Gmail, Google Drive, LinkedIn, Twitter, and more. --- ✅ Key Capabilities - AI Agent + Tool Use: Built using n8n's AI Agent and MCP system, enabling intelligent multi-step reasoning. - Tool Integration: - Google Calendar: schedule, update, delete events - Gmail: sea

Collect WhatsApp questionnaire responses in Postgres (Module "Anketa")

Who is this for? This workflow is designed for businesses or organizations looking to collect and store user responses from questionnaires via a WhatsApp bot, with data saved in a Postgres database. What problem is this workflow solving? This workflow streamlines the process of collecting and managing user responses to questionnaires. It helps automate data collection from multiple users and stores the responses in a centralized database for easy access and analysis. What this workflow does Basi

Enrich calendar events with AI analysis using OpenAI, Perplexity & Weather data

This template helps you manage your calendars by enriching each calendar event with data from Perplexity, OpenWeatherMap, & Open AI, and sending notifications on your Telegram. 🤖 Smart Calendar Agent: Enrich Calendar Events with AI Analysis using OpenAI, Perplexity & Weather Data Problem 😤 Calendar management is a NIGHTMARE. I waste hours manually checking weather, researching restaurants, remembering flight details, and missing important prep work for events—scattered, reactive, exhausting. I w

Process multiple prompts in parallel with Azure OpenAI Batch API

Process Multiple Prompts in Parallel with Azure OpenAI Batch API Who is this for? This workflow is designed for developers and data scientists who want to efficiently send multiple prompts to the Azure OpenAI Batch API and retrieve responses in a single batch process. It is particularly useful for applications that require processing large volumes of text data, such as chatbots, content generation, or data analysis. What problem is this workflow solving? Sending multiple prompts to the Azure Ope