Workflow Templates

💡 What It Is SmartReserve is a flexible, automated Telegram chatbot built in n8n that allows users to request and confirm reservations for any kind of resource—training sessions, equipment, appointments, event slots, or more. It connects with Google Sheets for live availability tracking and automatically sends confirmation emails to your users. ⚙️ How It Works Telegram Chatbot Interface Users interact with a friendly bot to submit their reservation request. The bot collects: Date Name Email Resource / Service Start Time & End Time Final confirmation All in one seamless message. Conflict-Free Booking System The bot checks your existing reservation sheet to avoid time overlaps before confirming. Google Sheets Integration Two spreadsheets are used: Resource Info: Define available services, resources, or assets. Reservation Log: Store confirmed reservations in structured rows. Confirmation via Email Once a reservation is accepted, the bot sends a detailed confirmation email to the user. 🚀 Setup Steps Import the n8n Workflow Use the provided .json template inside your n8n workspace. Create Your Google Sheets Sheet 1: Resource Info (e.g., rooms, courts, sessions, etc.) Sheet 2: Reservation Log with these headers: CopyEditDate | Name | Email | Resource | Start Time | End Time | Status Set Telegram Bot Token Create a Telegram bot and paste the token into n8n credentials. Connect Google Sheets Add your Google account to n8n and allow spreadsheet access. Customize for Your Use Case Rename “Resource” to anything (e.g., Room, Coach, Equipment). Edit confirmation text and branding inside the “Set” and “Email” nodes. Go Live! Enable the workflow, and you’re ready to accept real-time reservations. 📦 What You Get ✅ One-click Telegram reservation system ✅ Conflict checker with Google Sheets ✅ Auto email confirmation ✅ User-friendly one-shot data collection ✅ Fully editable & extendable workflow ✅ Future updates and support options 🙋 Need Help Setting It Up? If you'd like help customizing or deploying this workflow, I offer quick setup assistance and extended support.📧 Contact: tharwat.elsayed.hamad@gmail.com 💬 Whatsapp: +201061803236 Whether you're setting it up for your team, your club, or your business—I’m here to help!

This workflow is designed to generate prompts for AI agents and store them in Airtable. It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable. 2. Setup Instructions Prerequisites AI model eg Gemini, openAI etc** Airtable base and table or other storage tool** Step-by-Step Guide Clone the Workflow Copy the provided workflow JSON and import it into your n8n instance. Configure Credentials Set up the Google Gemini(PaLM) API account credentials. Set up the Airtable Personal Access Token account credentials. Map Airtable Base and Table Create a copy of the Prompt Library in Airtable. Map the Airtable base and table in the Airtable node. Customize Prompt Template Edit the 'Create prompt' node to customize the prompt template as needed. Configuration Options Prompt Template:** Customize the prompt template in the 'Create prompt' node to fit your specific use case. Airtable Mapping:** Ensure the Airtable base and table are correctly mapped in the Airtable node. 4. Running and Troubleshooting Running the Workflow Trigger the Workflow: Send a chat message to trigger the workflow. Monitor Execution: Use the n8n interface to monitor the workflow execution. Check Completion: Verify that the prompt is stored in Airtable and check the chat interface for the result. Troubleshooting Tips API Issues:** Ensure that the APIs and Airtable credentials are correctly configured. Data Mapping:** Verify that the Airtable base and table are correctly mapped. Prompt Template:** Check the prompt template for any errors or inconsistencies. Use Case Examples This workflow is particularly useful in scenarios where you want to automate the generation and management of AI agent prompts. Here are some examples: Rapid Prototyping of AI Agents: Quickly generate and test different prompts for AI agents in various applications. Content Creation:** Generate prompts for AI models that create blog posts, articles, or social media content. Customer Service Automation:** Develop prompts for AI-powered chatbots to handle customer inquiries and support requests. Educational Tools:** Create prompts for AI tutors or learning assistants. Industries/Professionals: Software Development:** Developers building AI-powered applications. Marketing:** Marketers automating content creation and social media management. Customer Service:** Customer service managers implementing AI-driven chatbots. Education:** Educators creating AI-based learning tools. Practical Value: Time Savings:** Automates the prompt generation process, saving significant time and effort. Improved Prompt Quality:** Leverages Google Gemini and structured prompt engineering principles to generate more effective prompts. Centralized Prompt Management:** Stores prompts in Airtable for easy access, organization, and reuse. 4. Running and Troubleshooting Running the Workflow:** Activate the workflow in n8n. Send a chat message to the webhook URL configured in the "When chat message received" node. Monitor the workflow execution in the n8n editor. Monitoring Execution:** Check the execution log in n8n to see the data flowing through each node and identify any errors. Checking for Successful Completion:** Verify that a new record is created in your Airtable base with the generated prompt, name, and category. Confirm that the "Return results" node sends back confirmation of the prompt in the chat interface. Troubleshooting Tips:** Error:** 400: Bad Request in the Google Gemini nodes: Cause:** Invalid API key or insufficient permissions. Solution:** Double-check your Google Gemini API key and ensure that the API is enabled for your project. Error:** Airtable node fails to create a record: Cause:** Invalid Airtable credentials, incorrect Base ID or Table ID, or mismatched column names. Solution:** Verify your Airtable API key, Base ID, Table ID, and column names. Ensure that the data types in n8n match the data types in your Airtable columns. Follow me on Linkedin for more

Auto-generate & post content using AI This workflow helps you create daily content using just a topic prompt. It writes a tweet, generates an image, and publishes across Twitter, Facebook, and LinkedIn — all on autopilot. How it works Triggers daily at 10 PM to start the flow Uses OpenAI to generate a niche topic title Writes a short-form post (tweet style) with hashtags Generates a Japanese anime-style image for visual context Saves everything in Google Sheets Publishes automatically on Twitter, LinkedIn, and Facebook Set up steps You’ll need OpenAI, Google Sheets, and social media credentials (Twitter, Facebook, LinkedIn) Takes about 10–15 minutes to configure if you already have the credentials ready Make sure your Sheet and API keys are properly linked before activating 📝 Keep detailed notes inside the workflow with sticky notes for easier handoff or collaboration.

Google Sheets Company Enrichment with Explorium MCP Template Download the following json file and import it to a new n8n workflow: google\_sheets\_enrichment.json Overview This n8n workflow template enables automatic enrichment of company information in your Google Sheets. When you add a new company or update existing company details (name or website), the workflow automatically fetches additional business intelligence data using Explorium MCP and updates your sheet with: Business ID NAICS industry code Number of employees (range) Annual revenue (range) Key Features Automatic Triggering**: Monitors your Google Sheet for new rows or updates to company name/website fields Smart Processing**: Only processes new or modified rows, not the entire sheet Data Validation**: Ensures both company name and website are present before processing Error Handling**: Processes each row individually to prevent one failure from affecting others Powered by AI**: Uses Claude Sonnet 4 with Explorium MCP for intelligent data enrichment Prerequisites Before setting up this workflow, ensure you have: n8n instance (self-hosted or cloud) Google account with access to Google Sheets Anthropic API key for Claude Explorium MCP API key Installation & Setup Step 1: Import the Workflow Create a new workflow. Download the workflow JSON from above. In your n8n instance, go to Workflows → Add Workflow → Import from File Select the JSON file and click Import Step 2: Create Google Sheet Create a new google sheet (or make a copy of this template) Your Google Sheet must have the following columns (exact names): name - Company name website - Company website URL business_id - Will be populated by the workflow naics - Will be populated by the workflow number_of_employees_range - Will be populated by the workflow yearly_revenue_range - Will be populated by the workflow Step 3: Configure Google Sheets Credentials You'll need to set up two Google credentials: Google Sheets Trigger Credentials: Click on the Google Sheets Trigger node Under Credentials, click Create New If working on n8n Cloud, Click the 'Sign in with Google' button Grant permissions to read and monitor your Google Sheets If working on n8n Instance, Follow the OAuth2 authentication process here Fill the Client ID and Client Secret fields Google Sheets Update Credentials: Click on the Update Company Row node Under Credentials, select the same credentials or create new ones (The same you did above) Ensure permissions include write access to your sheets Step 4: Configure Anthropic Credentials Click on the Anthropic Chat Model node Under Credentials, click Create New Enter your Anthropic API key Save the credentials Step 5: Configure Explorium MCP Credentials Click on the MCP Client node Under Credentials, click Create New (Header Auth) Fill the Name field with api_key Fill the Value field with your Explorium API Key Save the credentials Step 6: Link Your Google Sheet In the Google Sheets Trigger node: Select your Google Sheet from the dropdown Select the worksheet (usually "Sheet1") In the Update Company Row node: Select the same Google Sheet and worksheet Ensure the matching column is set to row_number Step 7: Activate the Workflow Click the Active toggle in the top right to activate the workflow The workflow will now monitor your sheet every minute for changes How It Works Workflow Process Flow Google Sheets Trigger: Polls your sheet every minute for new rows or changes to name/website fields Filter Valid Rows: Validates that both company name and website are present Loop Over Items: Processes each company individually AI Agent: Uses Explorium MCP to: Find the company's business ID Retrieve firmographic data (revenue, employees, NAICS code) Format Output: Structures the data for Google Sheets Update Company Row: Writes the enriched data back to the original row Trigger Behavior First Activation**: May process all existing rows to establish a baseline Ongoing Operation**: Only processes new rows or rows where name/website fields change Polling Frequency**: Checks for changes every minute Usage Adding New Companies Add a new row to your Google Sheet Fill in the name and website columns Within 1 minute, the workflow will automatically: Detect the new row Enrich the company data Update the remaining columns Updating Existing Companies Modify the name or website field of an existing row The workflow will re-process that row with the updated information All enrichment data will be refreshed Monitoring Executions In n8n, go to Executions to see workflow runs Each execution shows: Which rows were processed Success/failure status Detailed logs for troubleshooting Troubleshooting Common Issues All rows are processed instead of just new/updated ones Ensure the workflow is activated, not just run manually Manual test runs will process all rows First activation may process all rows once No data is returned for a company Verify the company name and website are correct Check if the company exists in Explorium's database Some smaller or newer companies may not have data available Workflow isn't triggering Confirm the workflow is activated (Active toggle is ON) Check that changes are made to the name or website columns Verify Google Sheets credentials have proper permissions Authentication errors Re-authenticate Google Sheets credentials Verify Anthropic API key is valid and has credits Check Explorium Bearer token is correct and active Error Handling The workflow processes each row individually, so if one company fails to enrich: Other rows will still be processed The failed row will retain its original data Check the execution logs for specific error details Best Practices Data Quality: Ensure company names and websites are accurate for best results Website Format: Include full URLs (https://example.com) rather than just domain names Batch Processing: The workflow handles multiple updates efficiently, so you can add several companies at once Regular Monitoring: Periodically check execution logs to ensure smooth operation API Limits & Considerations Google Sheets API**: Subject to Google's API quotas Anthropic API**: Each enrichment uses Claude Sonnet 4 tokens Explorium MCP**: Rate limits may apply based on your subscription Support For issues specific to: n8n platform**: Consult n8n documentation or community Google Sheets integration**: Check n8n's Google Sheets node documentation Explorium MCP**: Contact Explorium support for API-related issues Anthropic/Claude**: Refer to Anthropic's documentation for API issues Example Use Cases Sales Prospecting: Automatically enrich lead lists with company size and revenue data Market Research: Build comprehensive databases of companies in specific industries Competitive Analysis: Track and monitor competitor information Investment Research: Gather firmographic data for potential investment targets

🤖 AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI) This no-code workflow turns your Telegram bot into an intelligent, always-on AI support agent that references your business documentation in Google Docs to respond to customer queries—instantly and accurately. Watch full step-by-step video tutorial of the build here: https://youtu.be/Mlv7CjGO7wI 🔧 How it works: Telegram Trigger – Captures incoming messages from users on your Telegram bot Langchain AI Agent (OpenAI GPT) – Interprets the message and uses RAG (retrieval-augmented generation) techniques to craft an answer Google Docs Tool – Connects to and retrieves context from your specified Google Doc (e.g. FAQ, SOPs, policies) Memory Buffer – Keeps track of recent chat history for more human-like conversations Telegram Reply Node – Sends the AI-generated response back to the user 💡 Use Cases: E-commerce customer service SaaS product onboarding Internal helpdesk bot for teams WhatsApp-style support for digital businesses 🧠 What makes this powerful: Supports complex questions by referencing a live Google Doc knowledge base Works in plain conversational language (no buttons or forms needed) Runs 24/7 with zero code Easily extendable to Slack, WhatsApp, or email support 🛠️ Tools used: Telegram Node (trigger + send) Langchain Agent with OpenAI GPT Google Docs Tool Memory Buffer Sticky Notes for easy understanding

AI-Powered Daily Gmail Digest Summary using LangChain & OpenRouter This n8n template helps you automatically summarize your daily Gmail messages using OpenRouter's GPT model via LangChain. It generates a structured email digest highlighting key information, tasks, issues, and action items — all delivered to your inbox every morning. Who’s it for Busy professionals who want a quick overview of their daily emails Founders or managers needing to track team or client communication Anyone looking to automate inbox triage and reduce time spent on emails How it works / What it does This n8n workflow runs every morning at 7 AM, automatically: Fetches emails from the last 24 hours Collects important fields: sender, subject, and snippets Feeds them into an AI-powered agent (OpenRouter + LangChain) The AI: Extracts key topics, tasks, deadlines, and issues Formats the info clearly with a bullet-point summary Sends the final summarized report to your inbox How to set up Clone or import the workflow into your n8n instance Replace <Your Email ID> in the Code node with your actual Gmail address (or remove if not needed) Ensure your Gmail and OpenRouter credentials are set up in n8n Update the recipient email in the Send Summary node if you want it sent to a fixed address Activate the workflow once tested How to customize the workflow Change Summary Style:** Edit the system message in the LangChain Agent to match your tone (e.g. casual, business, detailed) Adjust Digest Time:** Change the Schedule Trigger to any preferred hour Customize Recipients:** Change or add recipients dynamically or statically in the Gmail send node Filter Email Type:** Modify the Gmail query in the Code node to include filters like from:, is:unread, subject:project

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database. Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw How it works A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook. The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base. The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses. On successful search results, the Agent can then use this information to answer the user's query. The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen. Finally, the response is sent back to the user through SMS using Twilio. How to use Ensure your Twilio number is set to forward messages to this workflow's webhook URL. Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business. Ask questions like: "Can you help me find suitable courses to fill my Wednesday mornings?" "Which courses are being instructed by profession Lee?" "I'm interested in creative arts. What courses are available which could be relevant to me?" Requirements Twilio for SMS receiving and sending OpenAI for LLM and Agent Airtable for Course Database Customising this workflow Add additional tools and expand the range of queries the agent is able to answer or assist with. Not using Airtable? This technique also works with SQL databases like PostgreSQL.

Overview This release introduces a Voice-Enabled Tour Recommendation System that leverages n8n, ElevenLabs Voice Agent, OpenAI GPT-4o, and Pinecone Vector DB to deliver personalized travel itineraries based on spoken input. Users speak their preferences to the ElevenLabs voice agent, which then triggers an n8n workflow that returns a tailored tour plan. Features Voice interaction with AI-powered travel agent via ElevenLabs Uses ChatGPT-4o for contextual understanding and generation Dynamic query handling with vector-based search using Pinecone Fast response generation using n8n webhook Modular agent memory and role design for scalable enhancement Pre-requisites n8n account with workflow creation access ElevenLabs account with agent and webhook setup OpenAI API key (GPT-4o access) Pinecone account for vector database A list of vectorized tour packages using this n8n embedder (https://creators.n8n.io/workflows/5085) Setup Instructions Step 1: Configure the Voice Agent Webhook in ElevenLabs Use POST method Webhook URL: https://... Breakdown voice input into: Destination Type of tour Number of days Number of passengers Step 2: Set Up the AI Agent Prompt in ElevenLabs Use a conversational style with summaries, clarifying questions, and affirmations. Example Prompt: “You use a natural speech style and periodically summarize... Your goal is to help callers create a personalized tour plan.” Step 3: Select LLM LLM: GPT-4o Mini Memory window: Up to 5 contexts Step 4: Integrate Tools Use Custom Tool: n8n ID: tool_xxxxxx Tool Description: “Generates travel plan once the details are collected” Step 5: Build n8n Workflow Trigger: Webhook (POST) Process user input: Tour Recommendation AI Agent Use OpenAI Chat Model (GPT-4o) for reasoning Query Pinecone Vector Store using Tour Builder Q&A node Respond with structured Itinerary Plan via webhook response How to use: Execute the n8n workflow (the webhook waits for the voice trigger from elevenlabs) Start the Elevenlabs Voice Agent Request for a tour plan to any destination giving the details of your tour preferences. Wait for the Voice Agent to respond back with tour package suggestions after fetching the tour details from the n8n workflow. Close the conversation. | Area | Improvement | | ------------------ | ----------------------------------------------------- | | 🔉 Voice UX | Natural-sounding travel agent using ElevenLabs | | 💡 Personalization | ChatGPT-4o adapts based on travel style & preferences | | 📚 Knowledge Base | Pinecone-powered vector retrieval of real tour data | | 🔁 Reusability | Modular workflow with reusable embedding tools | | ⚙️ System Design | Separation of memory, logic, and data layers | Who is this for? Travel Agencies & DMCs Offer ultra-personalized packages based on customer queries. Let AI do the matching. Tour Package Aggregators Auto-curate and send matching packages from your catalog — no manual searching needed. Content & Marketing Teams Craft customized tour recommendations for email campaigns and newsletters. Tech-enabled Travel Startups Embed this intelligence in your workflows, CRMs, or chatbots to delight customers.

Unlock a new level of sophistication for your AI agents with this template. While the native n8n Think Tool is great for giving an agent an internal monologue, it's limited to one instance. This workflow provides a clever solution using a sub-workflow to create multiple, custom thinking tools, each with its own specific purpose. This template provides the foundation for building agents that can plan, act, and then reflect on their actions before proceeding. Instead of just reacting, your agent can now follow a structured, multi-step reasoning process that you design, leading to more reliable and powerful automations. Who is this for? AI and automation developers:** Anyone looking to build complex, multi-tool agents that require robust logic and planning capabilities. LangChain enthusiasts:** Users familiar with advanced agent concepts like ReAct (Reason-Act) will find this a practical way to implement similar frameworks in n8n. Problem solvers:** If your current agent struggles with complex tasks, giving it distinct steps for planning and reflection can dramatically improve its performance. What problem does this solve? Bypasses the single "Think Tool" limit:** The core of this template is a technique that allows you to add as many distinct thinking steps to your agent as you need. Enables complex reasoning:** You can design a structured thought process for your agent, such as "Plan the entire process," "Execute Step 1," and "Reflect on the result," making it behave more intelligently. Improves agent reliability and debugging:** By forcing the agent to write down its thoughts at different stages, you can easily see its line of reasoning, making it less prone to errors and much easier to debug when things go wrong. Provides a blueprint for sophisticated AI:** This is not just a simple tool; it's a foundational framework for building state-of-the-art AI agents that can handle more nuanced and multi-step tasks. How it works The re-usable "Thinking Space": The magic of this template is a simple sub-workflow that does nothing but receive text. This workflow acts as a reusable "scratchpad." Creating custom thinking tools: In the main workflow, we use the Tool (Workflow) node to call this "scratchpad" sub-workflow multiple times. We give each of these tools a unique name (e.g., Initial thoughts, Additional thoughts). The power of descriptions: The key is the description you give each of these tool nodes. This description tells the agent when and how it should use that specific thinking step. For example, the Initial thoughts tool is described as the place to create a plan at the start of a task. Orchestration via system prompt: The main AI Agent's system prompt acts as the conductor, instructing the agent on the overall process and telling it about its new thinking abilities (e.g., "Always start by using the Initial thoughts tool to make a plan..."). A practical example: This template includes two thinking tools to demonstrate a "Plan and Reflect" cycle, but you can add many more to fit your needs. Setup Add your own "action" tools: This template provides the thinking framework. To make it useful, you need to give the agent something to do. Add your own tools to the AI Agent, such as a web search tool, a database lookup, or an API call. Customize the thinking tools: Edit the description of the existing Initial thoughts and Additional thoughts tools. Make them relevant to the new action tools you've added. For example, "Plan which of the web search or database tools to use." Update the agent's brain: Modify the system prompt in the main AI Agent node. Tell it about the new action tools you've added and how it should use your customized thinking tools to complete its tasks. Connect your AI model: Select the OpenAI Chat Model node and add your credentials. Taking it further Create more granular thinking steps:** Add more thinking tools for different stages of a process, like a "Hypothesize a solution" tool, a "Verify assumptions" tool, or a "Final answer check" tool. Customize the thought process:* You can change *how the agent thinks by editing the prompt inside the fromAI('Thoughts', ...) field within each tool. You could ask for thoughts in a specific format, like bullet points or a JSON object. Change the workflow trigger:** Switch the chat trigger for a Telegram trigger, email, Slack, whatever you need for your use case! Integrate with memory:** For even more power, combine this framework with a long-term memory solution, allowing the agent to reflect on its thoughts from past conversations.

Overview This automated workflow fetches Upwork job postings using Apify, removes duplicate job listings via Airtable, and sends new job opportunities to Slack. Key Features: Automated job retrieval** from Upwork via Apify API Duplicate filtering** using Airtable to store only unique jobs Slack notifications** for new job postings Runs every 30 minutes** during working hours (9 AM - 5 PM) This workflow requires an active Apify subscription to function, as it uses the Apify Upwork API to fetch job listings. Who is This For? This workflow is ideal for: Freelancers looking to track Upwork jobs in real time Recruiters automating job collection for analytics Developers who want to integrate Upwork job data into their applications What Problem Does This Solve? Manually checking Upwork for jobs is time-consuming and inefficient. This workflow: Automates job discovery based on your keywords Filters out duplicate listings, ensuring only new jobs are stored Notifies you on Slack when new jobs appear How the Workflow Works 1. Schedule Trigger (Every 20 Minutes) Triggers the workflow at 20-minute intervals Ensures job searches are only executed during working hours (9 AM - 5 PM) 2. Query Upwork for Jobs Uses Apify API to scrape Upwork job posts for specific keywords (e.g., "n8n", "Python") 3. Find Existing Jobs in Airtable Searches Airtable to check if a job (based on title and link) already exists 4. Filter Out Duplicate Jobs The Merge Node compares Upwork jobs with Airtable data The IF Node filters out jobs that are already stored in the database 5. Save Only New Jobs in Airtable The Insert Node adds only new job listings to the Airtable collection 6. Send a Slack Notification If a new job is found, a Slack message is sent with job details Setup Guide Required API Keys Upwork Scraper (Apify Token) – Get your token from Apify Airtable Credentials Slack API Token – Connect Slack to n8n and set the channel ID (default: #general) Configuration Steps Modify search keywords in the 'Assign Parameters' node (startUrls) Adjust the Working Hours in the 'If Working Hours' node Set your Slack channel in the Slack node Ensure Airtable is connected properly - you'll need to create a table with 'title' and 'link' columns. Adjust the 'If Working Hours' node to match your timezone and hours, or remove it altogether to receive notifications and updates constantly. How to Customize the Workflow Change keywords: update the startUrls in the 'Assign Parameters' node to track different job categories Change 'If Working Hours': Modify conditions in the IF Node to filter times based on your needs Modify Slack Notifications: Adjust the Slack message format to include additional job details Why Use This Workflow? Automated job tracking without manual searches Prevents duplicate entries in Airtable Instant Slack notifications for new job opportunities Customizable – adapt the workflow to different job categories Next Steps Run the workflow and test with a small set of keywords Expand job categories for better coverage Enhance notifications by integrating Telegram, Email, or a dashboard This workflow ensures real-time job tracking, prevents duplicates, and keeps you updated effortlessly.

Convert PDF documents to AI-generated podcasts with Google Gemini and Text-to-Speech Transform any PDF document into an engaging, natural-sounding podcast using Google's Gemini AI and advanced Text-to-Speech technology. This automated workflow extracts text content, generates conversational scripts, and produces high-quality audio files. Who is this for? This workflow template is perfect for content creators, educators, researchers, and marketing professionals who want to repurpose written content into audio format. Ideal for creating podcast episodes, educational content, or making documents more accessible. What problem does this solve? Converting written documents to engaging audio content manually is time-consuming and requires scriptwriting skills. This workflow automates the entire process, turning static PDFs into dynamic, conversational podcasts that sound natural and engaging. What this workflow does Extracts text from uploaded PDF documents Generates podcast script using Google Gemini AI with conversational tone Converts script to speech using Google's advanced TTS with customizable voices Processes audio into properly formatted WAV files Saves final podcast ready for distribution Setup Obtain API credentials: Get Google Gemini API key from AI Studio Configure credentials in n8n as "Google Gemini(PaLM) Api account" Configure voice settings: Choose from available voices: Kore (professional), Aoede (conversational), Laomedeia (energetic) Customize script generation prompts if needed Test the workflow: Upload a sample PDF file Verify audio output quality Adjust voice settings as preferred How to customize this workflow Modify script style:** Edit the prompt in the "Generate Podcast Script" node to change tone, length, or format Change voice:** Update the voice name in "Prepare TTS Request" node Add preprocessing:** Insert text cleaning nodes before script generation Integrate with storage:** Connect to Google Drive, Dropbox, or other storage services Add notifications:** Include Slack or email notifications when podcasts are ready Note: This template requires Google Gemini API access and works best with text-based PDF files under 10MB.

Overview In cold email campaigns, the lead's company name is the 2nd most frequently inserted variable after their first name. They're critical for effective cold email personalization. However, company names are often messy and can contain taglines, legal suffixes (e.g. LLC, Inc.), and other variations that would never be written out by a human in an email. If your email starts with "I came across Techwave Solutions LLC on LinkedIn...", it's a dead giveaway that you're sending a tempalted email and a response is much less likely. This simple workflow uses AI to clean up messy company names in a Google Sheet so that your cold email campaigns can achieve better results. How It Works A form is submitted with a Google Sheet url The workflow grabs the leads and uses an LLM node to clean the company names The updated leads are saved back in a new sheet within the original spreadsheet Setup Steps Add your Google Sheets and OpenAI (or your AI model provider of choice) credentials to n8n Create a Google Sheet with your list of leads. IMPORTANT: the sheet MUST have a column called "Company" (Optional). The AI workflow has a highly optimized system prompt. However, you may achieve better results by updating the list of examples in the prompt with companies (real or fake) in the industry you're targeting. If you have any questions or feedback about this workflow, or would like me to build custom workflows for your business, email me at n8n@paperjam.agency.