by Dmytro
AI-Powered Product Assistant for E-commerce Transform your online store customer service with an intelligent AI assistant that automatically processes customer inquiries, searches your product database, and provides personalized responses about product availability, pricing, and specifications. Perfect for shoe stores, fashion retailers, and any business with extensive product catalogs - this workflow eliminates manual customer service while increasing response speed and accuracy. How it works Customer sends product inquiry via webhook (Instagram DM, website chat, or messaging app) AI extracts key product details (brand, model, size, color) from natural language text System searches your Google Sheets product database with smart filtering AI generates friendly, personalized response with availability, pricing, and stock information Automatic response sent back to customer with product details or alternatives Screenshots: Customer inquiry: "Do you have Nike Air Max 40 size?" AI response: "Nike Air Max 90, size 40 - in stock 3 pieces, price 120$" Set up steps Prepare your product database - Create Google Sheets with columns: Brand, Model, Size, Color, Price, Quantity Configure AI settings - Connect OpenAI API for natural language processing Set up webhook endpoint - Configure trigger for your messaging platform (Instagram, Telegram, website chat) Test with sample inquiries - Verify AI correctly parses requests and finds products Deploy and monitor - Launch your automated assistant and track performance Time investment: 30-45 minutes setup, works immediately with any product catalog up to 1000+ items.
by Jimleuk
This n8n workflow shows how using multimodal LLMs with AI vision can tackle tricky image validation tasks which are near impossible to achieve with code and often impractical to be done by humans at scale. You may need image validation when users submitted photos or images are required to meet certain criteria before being accepted. A wine review website may require users only submit photos of wine with labels, a bank may require account holders to submit scanned documents for verification etc. In this demonstration, our scenario will be to analyse a set of portraits to verify if they meet the criteria for valid passport photos according to the UK government website (https://www.gov.uk/photos-for-passports). How it works Our set of portaits are jpg files downloaded from our Google Drive using the Google Drive node. Each image is resized using the Edit Image node to ensure a balance between resolution and processing speed. Using the Basic LLM node, we'll define a "user message" option with the type of binary (data). This will allow us to pass our portrait to the LLM as an input. With our prompt containing the criteria pulled off the passport photo requirements webpage, the LLM is able to validate the photo does or doesn't meet its criteria. A structured output parser is used to structure the LLM's response to a JSON object which has the "is_valid" boolean property. This can be useful to further extend the workflow. Requirements Google Gemini API key Google Drive account Customising this workflow Not using Gemini? n8n's LLM node works with any compatible multimodal LLM so feel free to swap Gemini out for OpenAI's GPT4o or Antrophic's Claude Sonnet. Don't need to validate portraits? Try other use cases such as document classification, security footage analysis, people tagging in photos and more.
by Naveen Choudhary
Description This workflow automates the process of scraping Google Events data using SerpApi and organizing it in Google Sheets for analysis and tracking. Who's it for Event organizers** who need to monitor competitor events in their area Marketing teams** tracking local events for partnership opportunities Researchers** collecting event data for analysis Business owners** monitoring industry events and conferences How it works The workflow searches Google Events using SerpApi's Google Events engine, processes the returned data, and saves it to a Google Sheets spreadsheet. It handles pagination automatically to collect multiple events and flattens the nested API response into a structured format. What it does Configures search parameters - Sets the search query, total events to fetch, and pagination settings Fetches events via SerpApi - Makes paginated requests to Google Events API with proper rate limiting Processes and flattens data - Transforms nested event data into a flat structure with all relevant fields Saves to Google Sheets - Appends the processed events to a Google Sheets document for easy analysis Requirements SerpApi account** with API key (Get one here) Google Sheets API access** (OAuth2 credentials) Google Sheets document** - Make a copy of this template sheet How to set up Configure SerpApi credentials in the HTTP Request node Set up Google Sheets OAuth2 authentication Update the Google Sheets document ID in the final node to point to your copy Modify search parameters in the "Set Search Parameters" node: Change query to your desired search terms Adjust total_events (10 events per page) Set start position for pagination Run the workflow using the manual trigger How to customize the workflow Search terms**: Modify the query in the Set node (e.g., "conferences in New York", "music events Los Angeles") Event count**: Adjust total_events to fetch more or fewer events Output format**: Modify the Google Sheets column mapping to include/exclude specific fields Rate limiting**: Adjust the requestInterval in the HTTP Request node if needed Scheduling**: Replace the Manual Trigger with a Schedule Trigger for automated runs Output data includes Event title, description, and direct link Start date and timing information Venue and address details Ticket information and pricing Event location map links Event images Original search query for tracking Note: This workflow respects SerpApi rate limits with built-in delays between requests and processes up to 10 events per API call efficiently.
by Jimleuk
This n8n workflow demonstrates how we can use Multimodal LLMs to parse and extract from PDF documents in n8n. In this particular scenario, we're passing a candidate's CV/resume to an AI which filters out unqualified applications. However, this sneaky candidate has added in hidden prompt to bypass our bot! Whatever will we do? No fret, using AI Vision is one approach to solve this problem... read on! How it works Our candidate's CV/Resume is a PDF downloaded via Google Drive for this demonstration. The PDF is then converted into an image PNG using a tool called Stirling PDF. Since the hidden prompt has a white font color, it is is invisible in the converted image. The image is then forwarded to a Basic LLM node to process using our multimodal model - in this example, we'll use Google's Gemini 1.5 Pro. In the Basic LLM node, we'll need to set a User Message with the type of Binary. This allows us to directly send the image file in our request. The LLM is now immune to the hidden prompt and its response is has expected. The example CV/Resume with hidden prompt can be found here: https://drive.google.com/file/d/1MORAdeev6cMcTJBV2EYALAwll8gCDRav/view?usp=sharing Requirements Google Gemini API Key. Alternatively, GPT4 will also work for this use-case. Stirling PDF or another service which can convert PDFs into images. Note for data privacy, this example uses a public API and it is recommended that you self-host and use a private instance of Stirling PDF instead. Customising the workflow Swap out the manual trigger for another trigger such as a webhook to integrate into your existing services. This example demonstrates a validation use-case ie. "does the candidate look qualified?". You can try additionally extracting data points instead such as years of experiences, previous companies etc.
by Nick Saraev
AI Proposal Generator System Categories* Sales Automation Document Generation AI Business Tools This workflow creates a complete AI-powered proposal generation system that transforms simple form inputs into professional, personalized proposals in under 30 seconds and can be deployed during live sales calls, allowing you to send polished proposals before the call even ends. Benefits* Instant Proposal Generation - Convert 30-second form inputs into professional proposals automatically High-Value Business Tool - Generates $1,500-$5,000 per client implementation Live Sales Integration - Generate and send proposals during active sales calls Complete Automation Pipeline - From form submission to email delivery with zero manual work Professional Presentation - Produces proposals indistinguishable from manually crafted documents Dual Platform Support - Works with both Google Slides (free) and PandaDoc (premium) integration How It Works* Smart Form Interface: Simple N8N form captures essential deal information Collects prospect details, problems, solutions, scope, timeline, and budget Designed for rapid completion during live sales conversations Advanced AI Processing: Uses sophisticated GPT-4 prompting with example-based training Converts basic form inputs into professionally written proposal sections Applies consistent tone, formatting, and business language automatically Dynamic Document Generation: Creates duplicate proposal templates for each new prospect Replaces template variables with AI-generated personalized content Maintains professional formatting and visual consistency Automated Email Delivery: Sends personalized email with proposal link immediately after generation Includes professional messaging and clear next steps Optionally includes invoice for immediate payment processing Premium PandaDoc Integration: Advanced version includes built-in payment processing Combines proposal, agreement, and invoice in single document Enables immediate signature and payment collection Business Use Cases* Service-Based Businesses - Generate proposals for consulting, agencies, and professional services Automation Agencies - Offer proposal generation as a high-value service to clients Sales Teams - Accelerate proposal creation and improve close rates Freelancers - Professionalize client interactions with instant custom proposals Consultants - Streamline business development with automated proposal workflows B2B Companies - Scale personalized proposal generation across entire sales organization Difficulty Level: Intermediate Estimated Build Time: 2-3 hours Monthly Operating Cost: $20-150 (depending on Google Slides vs PandaDoc) Watch My Complete Live Build* Want to see me build this entire $2,485 proposal system from scratch? I walk through every component live - including the AI prompting strategies, form design, Google Slides integration, and the advanced PandaDoc setup that enables payment collection. ๐ฅ See My Live Build Process: "I Built A $2,485 AI Proposal Generator In N8N (Copy This)" This comprehensive tutorial shows the real development process - including advanced AI prompting, template design, API integrations, and the exact pricing strategy that generates $1,500-$5,000 per client. Required Template Setup* Google Slides Template: Create a professional proposal template with these variable placeholders (wrapped in double curly braces): {{proposalTitle}} - Main proposal heading {{descriptionName}} - Project subtitle/description {{oneParagraphProblemSummary}} - Problem analysis section {{solutionHeadingOne}}, {{solutionHeadingTwo}}, {{solutionHeadingThree}} - Solution titles {{shortScopeTitleOne}} through {{shortScopeTitleThree}} - Scope sections {{milestoneOneDay}} through {{milestoneFourDay}} - Timeline milestones {{cost}} - Project pricing Form Field Requirements: The N8N form must include these exact field labels: First Name, Last Name, Company Name, Email, Website Problem (textarea) - Client's current challenges Solution (textarea) - Your proposed approach Scope (textarea) - Specific deliverables Cost - Project pricing How soon? - Timeline expectations PandaDoc Setup (Premium): Configure PandaDoc template with token placeholders matching the AI-generated content structure. Template must include pricing tables and signature fields for complete proposal-to-payment automation. Set Up Steps* Form Design & Integration: Create N8N form with optimized fields for proposal generation Design form flow for rapid completion during sales calls Configure form triggers and data validation AI Content Generation Setup: Configure OpenAI API for sophisticated proposal writing Implement example-based training with input/output pairs Set up JSON formatting for structured content generation Google Slides Integration (Free Version): Create professional proposal templates with variable placeholders Set up Google Cloud Console API access and credentials Configure template duplication and text replacement workflows Email Automation Setup: Configure Gmail integration for automated proposal delivery Design professional email templates with proposal links Set up dynamic content insertion and personalization PandaDoc Integration (Premium Version): Set up PandaDoc API for advanced document generation Configure payment processing and signature collection Implement proposal-to-payment automation workflows Testing & Quality Control: Test complete workflow with various proposal scenarios Validate AI output quality and professional presentation Optimize form fields and content generation based on results Advanced Features* Premium system includes: Payment Processing Integration: Collect payments immediately after proposal acceptance Digital Signature Collection: Streamline agreement execution with electronic signatures Custom Branding: Apply company branding and visual identity automatically Multi-Template Support: Generate different proposal types based on service offerings CRM Integration: Automatically sync proposal data with existing sales systems Why This System Works* The competitive advantage lies in speed and professionalism: 30-second generation time vs. hours of manual proposal writing Professional presentation that matches or exceeds manual proposals Live sales integration - send proposals during active conversations Consistent quality - eliminates human error and formatting inconsistencies Immediate follow-up - maintain sales momentum with instant delivery System Architecture* The workflow follows a simple but powerful 6-step process: Form Trigger - Captures essential deal information AI Processing - Converts inputs to professional content Template Duplication - Creates unique document for each prospect Content Replacement - Populates template with AI-generated content Email Delivery - Sends proposal with professional messaging Payment Collection (PandaDoc) - Enables immediate signature and payment Check Out My Channel* For more high-value automation systems and proven business-building strategies, explore my YouTube channel where I share the exact systems used to build successful automation businesses and scale to $72K+ monthly revenue.
by Yaron Been
๐ Automated Funding Intelligence: CrunchBase to Google Sheets Tracking Workflow! Workflow Overview This cutting-edge n8n automation is a sophisticated startup funding intelligence tool designed to transform market research into actionable insights. By intelligently connecting CrunchBase, data processing, and Google Sheets, this workflow: Discovers Funding Opportunities: Automatically retrieves latest funding rounds Tracks industry-specific investments Eliminates manual market research efforts Intelligent Data Processing: Filters funding data by location and industry Extracts key investment metrics Ensures comprehensive market intelligence Seamless Data Logging: Automatically updates Google Sheets Creates real-time investment database Enables rapid market trend analysis Scheduled Intelligence Gathering: Daily automated tracking Consistent market insight updates Zero manual intervention required Key Benefits ๐ค Full Automation: Zero-touch funding research ๐ก Smart Filtering: Targeted investment insights ๐ Comprehensive Tracking: Detailed funding intelligence ๐ Multi-Source Synchronization: Seamless data flow Workflow Architecture ๐น Stage 1: Funding Discovery Scheduled Trigger**: Daily market scanning CrunchBase API Integration** Intelligent Filtering**: Location-based selection Industry-specific focus Most recent funding rounds ๐น Stage 2: Data Extraction Comprehensive Metadata Parsing** Key Information Retrieval** Structured Data Preparation** ๐น Stage 3: Data Logging Google Sheets Integration** Automatic Row Appending** Real-Time Database Updates** Potential Use Cases Venture Capitalists**: Investment opportunity tracking Startup Scouts**: Market trend analysis Market Researchers**: Comprehensive funding insights Investors**: Strategic decision support Business Strategists**: Competitive landscape monitoring Setup Requirements CrunchBase API API credentials Configured access permissions Funding round tracking setup 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 ๐ค Advanced investment trend analysis ๐ Multi-source funding aggregation ๐ Customizable alert mechanisms ๐ Expanded industry coverage ๐ง 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 business privacy Use data for legitimate research Maintain transparent information gathering Provide proper attribution Hashtag Performance Boost ๐ #StartupFunding #InvestmentIntelligence #MarketResearch #AIWorkflow #DataAutomation #VentureCapital #TechInnovation #InvestmentTracking #BusinessIntelligence #StartupEcosystem Workflow Visualization [Daily Trigger] โฌ๏ธ [Fetch Funding Rounds] โฌ๏ธ [Extract & Format Data] โฌ๏ธ [Log to Google Sheets] Connect With Me Ready to revolutionize your funding intelligence? ๐ง Email: Yaron@nofluff.online ๐ฅ YouTube: @YaronBeen ๐ผ LinkedIn: Yaron Been Transform your market research with intelligent, automated workflows!
by Tomek
How it works Use Telegram to send in new phrases (flashcard front) You can also manually input phrase in the workflow itself ChatGPT generates provided phrase description (in English but you can change it) including multiple meanings & generates examples of using the phrase in a sample sentence (flashcard back) Steps to setup Provide your Telegram bot API key (optional) Provide your OpenAI key Provide Google Sheets credentials How to import flashcards from Google Sheets into Anki Use Google Sheets to Anki add-on: 1871608121 In Anki simply click Sync Decks and you're done :) Enjoy
by lin@davoy.tech
This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. profile Qwen2.5-Max 2:56 pm Hereโs a polished and detailed description for your "Daily Gratitude Reminder Bot for LINE" template, following the submission guidelines provided. This description is structured to meet all the requirements, including SEO optimization, clarity, and user convenience. Daily Gratitude Reminder Bot for LINE This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. Who Is This Template For? Developers who want to integrate AI-powered workflows into messaging platforms like LINE. Counselors & Therapists looking to encourage mindfulness and emotional well-being among their clients. Businesses & Organizations focused on employee wellness or customer engagement through positive reinforcement. Educators & Nonprofits seeking tools to promote mental health awareness and self-care practices. What Problem Does This Workflow Solve? Gratitude journaling has been proven to improve mental health, reduce stress, and increase overall happiness. However, many people struggle to maintain the habit due to busy schedules or forgetfulness. This workflow solves that problem by automating daily reminders to reflect on positive experiences, making it easier for users to build and sustain a gratitude practice. What This Workflow Does Scheduled Trigger: The workflow is triggered every evening at 9:00 PM using a schedule node. AI-Powered Message Generation: An Azure OpenAI Chat Model generates a unique and engaging reminder message with a temperature setting of 0.9 to ensure variety and creativity. Message Formatting: The generated message is reformatted to comply with the LINE Push API requirements, ensuring smooth delivery. Push Notification via LINE: The formatted message is sent to the user via the LINE Push API , delivering the reminder directly to their chat. Setup Guide Pre-Requisites Access to an Azure OpenAI account with credentials. A LINE Developers Console account with access to the Push API. Basic knowledge of n8n workflows and JSON formatting. How to Customize This Workflow to Your Needs Change the Time: Adjust the schedule trigger to send reminders at a different time. Modify the Prompt: Edit the AI model's input prompt to generate messages tailored to your audience (e.g., focus on work achievements or personal growth). Expand Recipients: Update the LINE Push API node to send reminders to multiple users or groups. Integrate Additional Features: Add nodes to log user responses or track engagement metrics. Why Use This Template? Promotes Mental Wellness: Encourages users to reflect on positive experiences, improving emotional well-being. Highly Customizable: Easily adapt the workflow to suit different audiences and use cases. Scalable: Send reminders to one user or thousands, making it suitable for both personal and organizational use. AI-Powered Creativity: Avoid repetitive messages by leveraging AI to generate fresh and engaging content.
by Oneclick AI Squad
This workflow auto-fetches top financial headlines, cleans the content, and uses AI to summarize it into a short investor-friendly email. Good to know The workflow runs daily and relies on stable webpage access; check the URL (e.g., https://www.ft.com/) for availability. AI costs may apply depending on the LLM model used (e.g., GPT-4 or Gemini); refer to provider pricing. How it works Trigger the workflow daily with the Schedule Daily Trigger node. Fetch financial news from a webpage using the Fetch Webpage News node. Add a Delay to Ensure Page Load node to ensure content is fully loaded. Extract and clean headlines with the Extract News Headlines & Clean Extracted Data node. Process the data with the LLM Chat Model node to generate a summary. Send the summarized report via email using the Email Daily Financial Summary node. How to use Import the workflow into n8n and configure the nodes with your webpage URL and email credentials. Test the workflow to verify content fetching and email delivery. Requirements Webpage access (e.g., financial news site API or RSS) Email service (e.g., SMTP or API) LLM model credentials (e.g., GPT-4 or Gemini) Customising this workflow Adjust the Fetch Webpage News node to target different news sources or modify the LLM Chat Model prompt for a different summary style.
by Pavel Duchovny
Who is this for? This workflow is designed for: Database administrators and developers working with MongoDB Content managers handling movie databases Organizations looking to implement AI-powered search and recommendation systems Developers interested in combining LangChain, OpenAI, and MongoDB capabilities What problem does this workflow solve? Traditional database queries can be complex and require specific MongoDB syntax knowledge. This workflow addresses: The complexity of writing MongoDB aggregation pipelines The need for natural language interaction with movie databases The challenge of maintaining user preferences and favorites The gap between AI language models and database operations What this workflow does This workflow creates an intelligent agent that: Accepts natural language queries about movies Translates user requests into MongoDB aggregation pipelines Queries a movie database containing detailed information including: Plot summaries Genre classifications Cast and director information Runtime and release dates Ratings and awards Provides contextual responses using OpenAI's language model Allows users to save favorite movies to the database Maintains conversation context using a window buffer memory Setup Required Credentials: OpenAI API credentials MongoDB connection details Node Configuration: Configure the MongoDB connection in the MongoDBAggregate node Set up the OpenAI Chat Model with your API key Ensure the webhook trigger is properly configured for receiving chat messages Database Requirements: A MongoDB collection named "movies" with the specified document structure Proper indexes for efficient querying Appropriate user permissions for read/write operations How to customize this workflow Modify the Document Structure: Update the tool description in the MongoDBAggregate node to match your collection schema Adjust the aggregation pipeline templates for your specific use case Enhance the AI Agent: Customize the prompt in the "AI Agent - Movie Recommendation" node Modify the window buffer memory size based on your context needs Add additional tools for more functionality Extend Functionality: Add more MongoDB operations beyond aggregation Implement additional workflows for different types of queries Create custom error handling and validation Add user authentication and rate limiting Integration Options: Connect to external APIs for additional movie data Add webhook endpoints for different platforms Implement caching mechanisms for frequent queries Add data transformation nodes for specific output formats This workflow serves as a foundation that can be adapted to various use cases beyond movie recommendations, such as e-commerce product search, content management systems, or any scenario requiring intelligent database interaction.
by ibrhdotme
Learning something new? Endlessly searching to find the best resources? This workflow finds top community-recommended learning resources on any topic from Hacker News, delivered to your inbox. How it works User submits a topic they want to learn via a simple form. The workflow searches for relevant "Ask HN" posts on Hacker News and extracts top-level comments. An LLM analyzes the comments and identifies the best learning resources. A personalized email is sent to the user with a Markdown formatted list of top recommendations, categorized by resource type (e.g., book, course, article) and difficulty level. Set up steps Add your Google Gemini API credentials. You'll need to create a project and enable the Generative Language API. Add your SMTP credentials for sending emails. Customize the Form and email subject (optional) Activate the workflow Screenshots for Workflow, Form and Email Built on Day-03 as part of the #100DaysOfAgenticAi Fork it, tweak it, have fun!
by Mauricio Perera
Overview: This workflow is designed to handle user inputs via a webhook, process the inputs with the Google Gemini API (specifically the gemini-2.0-flash-thinking-exp-1219 model), and return a structured response to the user. The response includes three key elements: reasoning, the final answer, and citation URLs (if applicable). This workflow provides a robust solution for integrating AI reasoning into your processes. This workflow can be utilized as a tool for AI-based agents, intelligent email drafting systems, or as a standalone intelligent automation solution. Setup: Webhook Configuration: Ensure the webhook node is properly set up to accept GET requests with an input parameter. Verify that the webhook path matches your application requirements. Test the webhook using tools like Postman to ensure proper data formatting. Google Gemini API Credentials: Set up your Google Gemini API account credentials in the HTTP Request node. Ensure API access and permissions are valid. Parameter Adjustments: Customize the temperature, topK, topP, and maxOutputTokens parameters to fit your use case. Customization: Input Parameters: Modify the webhook path or parameters based on the data your application will send. Response Formatting: Adjust the JavaScript code in the "Process API Response" node to fit your desired output structure. Output Expectations: Test the response returned by the "Return Response to User" node to ensure it meets your application requirements. Workflow Steps: Receive User Input: Node Type: Webhook Purpose: Captures a GET request containing a user-provided input parameter. Acts as the starting point for the workflow. Send Request to Google Gemini: Node Type: HTTP Request Purpose: Sends the received input to the Gemini-2.0-flash-thinking-exp-1219 model for processing. The API configuration includes parameters for customizing the response. Process API Response: Node Type: Code Node Purpose: Extracts reasoning, the final answer, and citation URLs from the API response. Organizes the output for further use. Return Response to User: Node Type: Respond to Webhook Purpose: Sends the processed and structured response back to the user via the webhook. Ensures the response format meets expectations. Expected Outcomes: Input Handling:** Successfully captures user input via a webhook. AI Processing:* Generates a structured response using the *Gemini-2.0-flash-thinking-exp-1219** model, including reasoning, answers, and citations (if available). Output Delivery:** Returns a user-friendly response formatted to your specifications. Notes: The workflow is inactive by default. Each node is annotated with a Sticky Note to clarify its purpose. Ensure all API credentials are correctly configured before execution. Use this workflow to save time, improve accuracy, and automate repetitive tasks efficiently. Tags: Automation Google Gemini AI Agents Intelligent Automation Content Generation Workflow Integration