Workflow Templates

Who this is for? Extract & Summarize Yelp Business Review is an automated workflow that extracts the Yelp business reviews using Bright Data Web Unlocker, process and formats the raw data, summarizes using the Google Gemini's LLM, and forward the concise summary with the review respose to a specified webhook endpoint. This workflow is tailored for: Local SEO Specialists who need structured insights from Yelp reviews to optimize listings. Business Owners wanting quick summaries of what customers love or complain about. Reputation Managers who monitor brand sentiment and identify customer pain points. Data Analysts & Researchers extracting Yelp review patterns at scale. AI Product Builders needing clean Yelp review data as input for their LLMs or recommender systems. What problem is this workflow solving? Yelp reviews are rich in customer sentiment but messy to work with manually. This workflow solves: The pain of scraping Yelp review content manually. The challenge of building the structured data with the summary. The need for structured outputs suitable for analysis, reports, or AI input. What this workflow does This automated pipeline does the following: Bright Data Integration**: Queries Yelp and scrapes business listing data using Bright Data's Web Unlocker. Structured Data Formatting**: Formats the Yelp review data to a structured response in JSON format. Google Gemini Summarization**: Sends the cleaned reviews to Google Gemini to: Output Delivery**: Returns the structured response with the concise summary over the webhook endpoint. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Yelp Business Review URL with the Bright Data zone by navigating to the Set Yelp URL with the Bright Data Zone node. Update the Webhook Notifier for the merged response node with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you’re a market researcher, entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Target Specific Business Categories** Update the Yelp Business Review input to scrape different businesses like gyms, salons etc. Limit Reviews** Add filters by description, location, page range to get the top reviews. Tweak the Data Extraction Node** Update the Structured Data Extractor node Output Parser for building the JSON response with the appropriate fields or attributes. Tweak the Summarization Prompt** Modify the Gemini prompt to generate a comprehensive summary. Send Output to Other Destinations** Replace the Webhook URL to forward output to: Google Sheets Airtable Slack or Discord Custom API endpoints

This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditiona OCR because: It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to any schema or language you desire! How it works You can use the example bank statement created specifically for this workflow here: https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing A PDF bank statement is imported via Google Drive. For this demo, I've created a mock bank statement which includes complex table layouts of 5 columns. Typically, OCR will be unable to align the columns correctly and mistake some deposits for withdrawals. Because multimodal LLMs do not accept PDFs directly, well have to convert the PDF to a series of images. We can achieve this by using a tool such as Stirling PDF. Stirling PDF is self-hostable which is handy for sensitive data such as bank statements. Stirling PDF will return our PDF as a series of JPGs (one for each page) in a zipped file. We can use n8n's decompress node to extract the images and ensure they are ordered by using the Sort node. Next, we'll resize each page using the Edit Image node to ensure the right balance between resolution limits and processing speed. Each resized page image is then passed into the Basic LLM node which will use our multimodal LLM of choice - Gemini 1.5 Pro. In the LLM node's options, we'll add a "user message" of type binary (data) which is how we add our image data as an input. Our prompt will instruct the multimodal LLM to transcribe each page to markdown. Note, you do not need to do this - you can just ask for data points to extract directly! Our goal for this template is to demonstrate the LLMs ability to accurately read the page. Finally, with our markdown version of all pages, we can pass this to another LLM node to extract required data such as deposit line items. Requirements Google Gemini API for Multimodal LLM. Google Drive access for document storage. Stirling PDF instance for PDF to Image conversion Customising the workflow At time of writing, Gemini 1.5 Pro is the most accurate in text document parsing with a relatively low cost. If you are not using Google Gemini however you can switch to other multimodal LLMs such as OpenAI GPT or Antrophic Claude. If you don't need the markdown, simply asking what to extract directly in the LLM's prompt is also acceptable and would save a few extra steps. Not parsing any bank statements any time soon? This template also works for Invoices, inventory lists, contracts, legal documents etc.

Who is this for This workflow is perfect for teams and individuals who manage extensive data in Notion and need a quick, AI-powered way to interact with their databases. If you're looking to streamline your knowledge management, automate searches, and get faster insights from your Notion databases, this workflow is for you. It’s ideal for support teams, project managers, or anyone who needs to query specific data across multiple records or within individual pages of their Notion setup. Check out the Notion template this Assistant is set up to use: https://www.notion.so/templates/knowledge-base-ai-assistant-with-n8n How it works The Notion Database Assistant uses an AI Agent built with Retrieval-Augmented Generation (RAG) to query this Knowledge Base style Notion database. The assistant can search across multiple properties like tags or question and retrieves content from inside individual Notion pages for additional context. Key features include: Querying the database with flexible filters. Searching within individual Notion pages and extracting relevant blocks. Providing a reference link to the exact Notion pages used to inform its responses, ensuring transparency and easy verification. This assistant uses two HTTP request tools—one for querying the Notion database and another for pulling data from within specific pages. It streamlines knowledge retrieval, offering a conversational, AI-driven way to interact with large datasets. Set up Find basic set up instructions inside the workflow itself or watch a quickstart video 👇

AI Research Assistant via Telegram (GPT-4o mini + DeepSeek R1 + SerpAPI) 👥 Who’s it for This workflow is perfect for anyone who wants to receive AI-powered research summaries directly on Telegram. Ideal for people asking frequent product, tech, or decision-making questions and want up-to-date answers sourced from the web. 🤖 What it does Users send a question via Telegram. An AI agent (DeepSeek R1) reformulates and understands the intent, while a second agent (GPT-4o mini) performs live research using SerpAPI. The most relevant answers, including links and images, are delivered back via Telegram. ⚙️ How it works 📲 Telegram Trigger – Starts when a user sends a message to your Telegram bot. 🧠 DeepSeek R1 Agent – Understands, clarifies, or reformulates the user query. 🧠 Research AI Agent (GPT-4o mini + SerpAPI) – Searches the web and summarizes the best results. 📤 Send Telegram Message – Sends the response back to the same user. 📋 Requirements Telegram bot (via BotFather) with API token set in n8n credentials OpenAI account with API key and balance for GPT-4o mini SerpAPI account (100 free searches/month) with API key DeepSeek account with API key and balance 🛠️ How to set up Create your Telegram bot using BotFather and connect it using the Telegram Trigger node Set up DeepSeek credentials and add a Chat Model AI Agent node using DeepSeek R1 to reformulate the user’s question Set up OpenAI credentials and add a second ChatGPT AI Agent node using GPT-4o mini In the GPT-4o node, enable the SerpAPI Tool and add your SerpAPI API key Pass the reformulated question from DeepSeek to the GPT-4o agent for live search and summarization Format the response (text, links, optional images) Send the final reply to the user using the Telegram Send Message node Ensure your n8n instance is publicly accessible Test the workflow by sending a message to your Telegram bot ✅

Auto-Publish Social Videos to 9 Platforms via Google Sheets and Blotato Who is this workflow for? This workflow is ideal for marketers, content creators, virtual assistants, and automation specialists managing multi-platform video content. It’s especially useful for teams who want to centralize publishing via a spreadsheet and automate social distribution in one shot. What problem does this workflow solve? Manually posting videos to multiple social platforms is tedious and time-consuming. This workflow allows you to streamline video distribution using Blotato’s API — no more switching between platforms or re-uploading the same video multiple times. What this workflow does This automation reads video metadata (URL, caption, title) from a Google Sheet, uploads the video to Blotato, and automatically publishes it to Instagram, YouTube, TikTok, Facebook, LinkedIn, Threads, Twitter (X), Pinterest, and Bluesky. It also updates the sheet to reflect the publishing status (STATUS = DONE), ensuring that your data remains clean and trackable. Setup Set up your Google Sheet with the required columns: PROMPT, DESCRIPTION, URL VIDEO, Titre, row_number, and STATUS. Add your Blotato API key in the headers of the Upload Video and Post to X nodes. Replace the platform-specific IDs in the Assign Social Media IDs node (Instagram ID, Facebook Page ID, etc.). Set the schedule in the Schedule Trigger node to define when the publishing happens. > ⚠️ Disclaimer: This workflow uses Community Nodes. These are only available on self-hosted n8n instances. How to customize this workflow Add logic to skip rows already marked as DONE. Expand to more platforms supported by Blotato. Use a webhook or Telegram trigger instead of the scheduler for more interactivity. Modify content per platform if needed (caption formatting, hashtags, etc.). 📄 Documentation: Notion Guide Demo Video 🎥 Watch the full tutorial here: YouTube Demo

Transform your local N8N instance into a powerful chat interface using any local & private Ollama model, with zero cloud dependencies ☁️. This workflow creates a structured chat experience that processes messages locally through a language model chain and returns formatted responses 💬. How it works 🔄 💭 Chat messages trigger the workflow 🧠 Messages are processed through Llama 3.2 via Ollama (or any other Ollama compatible model) 📊 Responses are formatted as structured JSON ⚡ Error handling ensures robust operation Set up steps 🛠️ 📥 Install N8N and Ollama ⚙️ Download Ollama 3.2 model (or other model) 🔑 Configure Ollama API credentials ✨ Import and activate workflow This template provides a foundation for building AI-powered chat applications while maintaining full control over your data and infrastructure 🚀.

This n8n template demonstrates how easy it is to build an Outlook Calendar Assistant powered by an AI agent equipped with Tools. For teams using Outlook Calendar and Slack who need easier calendar management, this workflow can be a great first step to introducing powerful AI tools into your daily activities. How it works A Slack Trigger node is configured to catch "bot mentions" events in a designated channel. The message is parsed using the Edit fields node to extract only the required attributes of the event. An AI Agent equipped with Outlook Calendar Tools enables question and answer capability for the organisation's shared calendars and events. The AI agent's response is sent back to Slack as a reply to the user's query. How to use The workflow is triggered via @mention-ing the bot followed by the query. eg. "@bot how many meetings does Paul have to attend to this week?" To start listening to real mentions, you must activate the workflow and set it to production mode. You must use the production webhook URL for the event subscription. Some sample queries to try "What's included in the product team's sprint demo this week?" "Who's booked room 7 for this Thursday?" "When is Jim & Nik's sales meeting with Microsoft?" Requirements Slack for Chat and Trigger. To get connected to Slack, see the official n8n docs for Slack Credentials. Outlook for Agent Tools To get connected to Outlook, see the official n8n docs for Outlook Credentials. Customising this workflow Not using Slack? This template can be modified to work with Teams but requires a little more configuration. Agents can have any number of tools but an overloaded agent is prone to confusion! If this happens, try splitting into multiple agents serving separate needs.

AI Database Assistant with Smart Query's & PostgreSQL Integration Description: 🚀 Transform Your Database into an Intelligent AI Assistant This workflow creates a smart database assistant that safely handles natural language queries without crashing your system. Features dual-agent architecture with built-in query limits and PostgreSQL optimization – perfect for commercial applications! ✅ Ideal for: SaaS developers building database search features 🔍 Database administrators providing safe AI access 🛡️ Business teams needing user-friendly data queries 📊 Anyone wanting ChatGPT-like database interaction 🤖 🔧 How It Works 1️⃣ User asks a question – "Show me top 10 popular products" 2️⃣ Main AI Agent – Interprets the request and ensures safety limits 3️⃣ SQL Sub-Agent – Generates precise PostgreSQL queries 4️⃣ Database executes – Returns formatted, limited results safely ⚡ Setup Instructions 1️⃣ Prepare Your Database Ensure PostgreSQL is accessible from n8n Note your table structure and column names Set up database connection credentials 2️⃣ Customize the Templates Replace [YOUR_TABLE_NAME] with your actual table name Update [YOUR_FIELDS] with your column names Modify examples to match your use case Important**: Keep all LIMIT clauses intact! 3️⃣ Configure the Agents Copy Main Agent system message to your primary AI node Copy Sub-Agent system message to your SQL generator node Connect the sub-workflow between both agents 4️⃣ Test & Deploy Test with sample queries like "Show me 5 recent items" Verify query limits work (max 50 results) Deploy and monitor performance 🎯 Why Use This Workflow? ✔️ System Protection – Built-in limits prevent crashes from large queries ✔️ Natural Language – Users ask questions in plain English ✔️ Commercial Ready – Generic templates work with any database ✔️ Dual-Agent Safety – Smart interpretation + precise SQL generation ✔️ PostgreSQL Optimized – Handles complex schemas and data types 🚨 Critical Features Query Limits**: Default 10, maximum 50 results (can be modified) Error Prevention**: No unlimited data retrieval Smart Routing**: Natural language → Safe SQL → Formatted results Customizable**: Works with any PostgreSQL database schema 🔗 Start building your AI database assistant today – safe, smart, and scalable!

🚀 Automated Founder Discovery: CrunchBase to Gmail Outreach Workflow! Workflow Overview This cutting-edge n8n automation is a sophisticated founder intelligence and outreach tool designed to transform startup research into actionable networking opportunities. By intelligently connecting CrunchBase, OpenAI, and Gmail, this workflow: Discovers Startup Founders: Automatically retrieves founder profiles Tracks latest company updates Eliminates manual research efforts Intelligent Profile Processing: Extracts key professional information Filters most relevant details Prepares comprehensive founder insights AI-Powered Summarization: Generates professional email-ready summaries Crafts personalized outreach content Ensures high-quality communication Seamless Email Distribution: Sends automated founder digests Integrates with Gmail Enables rapid professional networking Key Benefits 🤖 Full Automation: Zero-touch founder research 💡 Smart Profiling: Intelligent founder insights 📊 Comprehensive Intelligence: Detailed professional summaries 🌐 Multi-Platform Synchronization: Seamless data flow Workflow Architecture 🔹 Stage 1: Founder Discovery Manual Trigger**: Workflow initiation CrunchBase API Integration**: Profile retrieval Intelligent Filtering**: Identifies key startup founders Prepares for detailed analysis 🔹 Stage 2: Profile Extraction Detailed Information Capture** Key Field Mapping** Structured Data Preparation** 🔹 Stage 3: AI Summarization OpenAI GPT Processing** Professional Summary Generation** Contextual Insight Creation** 🔹 Stage 4: Email Distribution Gmail Integration** Automated Outreach** Personalized Communication** Potential Use Cases Venture Capitalists**: Startup scouting Sales Teams**: Lead generation Recruitment Specialists**: Talent discovery Networking Professionals**: Strategic connections Startup Ecosystem Researchers**: Market intelligence Setup Requirements CrunchBase API API credentials Configured access permissions Founder tracking setup OpenAI API GPT model access Summarization configuration API key management Gmail Account Connected email Outreach email configuration Appropriate sending permissions n8n Installation Cloud or self-hosted instance Workflow configuration API credential management Future Enhancement Suggestions 🤖 Advanced founder scoring 📊 Multi-source intelligence gathering 🔔 Customizable alert mechanisms 🌐 Expanded networking platform integration 🧠 Machine learning insights generation Technical Considerations Implement robust error handling Use secure API authentication Maintain flexible data processing Ensure compliance with API usage guidelines Ethical Guidelines Respect professional privacy Maintain transparent outreach practices Ensure appropriate communication Provide opt-out mechanisms Hashtag Performance Boost 🚀 #StartupNetworking #FounderDiscovery #AIOutreach #ProfessionalNetworking #TechInnovation #BusinessIntelligence #AutomatedResearch #StartupScouting #ProfessionalGrowth #NetworkingTech Workflow Visualization [Manual Trigger] ⬇️ [Updated Profiles List] ⬇️ [Founder Profiles] ⬇️ [Extract Key Fields] ⬇️ [AI Summarization] ⬇️ [Send Email] Connect With Me Ready to revolutionize your professional networking? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been Transform your founder research with intelligent, automated workflows!

Workflow Overview This sophisticated n8n automation is a powerful LinkedIn engagement and networking tool designed to revolutionize professional social media interaction. By intelligently combining web scraping, AI, and automation technologies, this workflow: Discovers Relevant Content: Automatically scrapes LinkedIn posts Identifies target profiles and recent content Ensures consistent networking opportunities Generates Intelligent Interactions: Uses AI to craft contextual, professional comments Ensures human-like, valuable engagement Maintains professional tone and relevance Automates Engagement Process: Likes and comments on selected posts Increases visibility and connection potential Builds professional network systematically Comprehensive Activity Tracking: Logs all interactions in Google Sheets Provides transparent engagement history Enables performance analysis and optimization Key Benefits 🤖 Full Automation: Consistent daily networking 💡 AI-Powered Interactions: Intelligent, context-aware engagement 📊 Detailed Tracking: Comprehensive interaction logging 🌐 Professional Visibility: Strategic online presence management Workflow Architecture 🔹 Stage 1: Content Discovery Scheduled Trigger**: Daily post scanning Phantombuster Integration**: LinkedIn post scraping Targeted Profile Research**: Identifies recent posts Extracts critical post metadata 🔹 Stage 2: AI-Powered Interaction OpenAI GPT Model**: Generates contextual comments Intelligent Analysis**: Understands post content Crafts personalized responses Professional Tone Maintenance** 🔹 Stage 3: Engagement Automation Automated Liking**: Increases post visibility Intelligent Commenting**: Posts AI-generated comments Ensures meaningful interaction 🔹 Stage 4: Performance Logging Google Sheets Integration** Comprehensive Activity Tracking** Interaction History Preservation** Potential Use Cases Sales Professionals**: Lead generation and networking Marketers**: Increased brand visibility Recruiters**: Talent discovery and engagement Entrepreneurs**: Professional network expansion Content Creators**: Audience interaction and growth Setup Requirements Phantombuster Account API key Configured LinkedIn scraping agents Profile URL list OpenAI API GPT model access API key for comment generation Preferred language model Google Sheets Connected Google account Prepared tracking spreadsheet Appropriate sharing settings n8n Installation Cloud or self-hosted instance Workflow configuration API credential management Future Enhancement Suggestions 🤖 Advanced sentiment analysis 📊 Engagement performance metrics 🎯 Intelligent post targeting 🔍 Machine learning optimization 🌐 Multi-platform support Technical Considerations Implement robust error handling Use exponential backoff for API calls Maintain flexible engagement strategies Ensure compliance with platform guidelines Ethical Guidelines Respect professional networking etiquette Maintain genuine, value-adding interactions Avoid spammy or repetitive engagement Prioritize quality over quantity Connect With Me Ready to revolutionize your professional networking? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been Transform your LinkedIn strategy with intelligent, automated workflows! #LinkedInAutomation #AINetworking #ProfessionalGrowth #CareerStrategy #NetworkingTech #AIMarketing #ProfessionalDevelopment #SocialMediaStrategy #ContentEngagement #BusinessIntelligence

Scrape Competitor Reviews & Generate Ad Creatives with Bright data and OpenAI How the Flow Runs Fill the Form Enter the Amazon product URL to analyze competitor reviews. Trigger Bright Data Scraper Bright Data scrapes Amazon reviews based on the provided URL. Wait for Snapshot Completion Periodically checks Bright Data until the scraping is complete. Retrieve JSON Data Collects the scraped review data in JSON format. Save Reviews to Google Sheets Automatically appends the scraped reviews to your Google Sheets. Aggregate Reviews Consolidates all reviews into a single summary for simpler analysis. Analyze Reviews with OpenAI LLM Sends the aggregated reviews to OpenAI (GPT-4o mini) to summarize competitors’ main weaknesses clearly. Generate Creative Ad Image OpenAI generates a visually appealing 1080x1080 ad image addressing these identified pain points. Send Ad Creative via Gmail Automatically emails the creative and review summary to your media buying team for immediate use in Meta ads. What You Need Google Sheets:** Template Bright Data:** Dataset and API key: www.brightdata.com OpenAI API Key:** For GPT-4o mini or your preferred LLM Automation Tool:** Ensure it supports HTTP Requests, Wait, Conditional (If), Google Sheets integration, Form Trigger, OpenAI integration, and Gmail integration. Form Fields to Fill Amazon Product URL:** Enter the competitor’s product URL from Amazon. Setup Steps Copy the provided Google Sheet template. Import the JSON workflow into your automation tool. Update credentials for Bright Data, Google Sheets, Gmail, and OpenAI. Test manually by submitting the form and verifying functionality. Optional: Set a schedule for regular workflow execution. Bright Data Trigger Example [ { "url": "https://www.amazon.com/example-product" } ] Tips Frequently update URLs to ensure fresh insights. Allow more wait time for extensive data scrapes. Focus on targeted products to optimize cost-efficiency. Need Help? Email: Yaron@nofluff.online Resources: YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Bright Data Documentation: https://docs.brightdata.com/introduction

Automated system that aggregates job postings from Upwork based on your criteria and delivers personalized notifications, helping you never miss relevant opportunities. 🚀 What It Does Custom job search based on keywords, skills, and categories Real-time job posting monitoring Smart filtering and prioritization Multi-channel notifications (Email/Slack/Teams) Duplicate detection 🎯 Perfect For Freelancers seeking new opportunities Agencies looking for projects Recruiters sourcing talent Business owners finding contractors Digital nomads ⚙️ Key Benefits ✅ Save hours of manual searching ✅ Get notified about relevant jobs first ✅ Never miss perfect opportunities ✅ Customizable search criteria ✅ Time-zone friendly notifications 🔧 What You Need Upwork account n8n instance Preferred notification channels setup 📊 Features Custom keyword alerts Budget range filtering Client history analysis Job type filtering (hourly/fixed) Experience level filtering 🛠️ Setup & Support Quick Setup Be up and running in 15 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Transform your freelance career with automated job hunting. Spend less time searching and more time winning projects.