by Jihene
AI-Agent Code Review for GitHub Pull Requests Description: This n8n workflow automates the process of reviewing code changes in GitHub pull requests using an OpenAI-powered agent. It connects your GitHub repo, extracts modified files, analyzes diffs, and uses an AI agent to generate a code review based on your internal code best practices (fed from a Google Sheet). It ends by posting the review as a comment on the PR and tagging it with a visual label like β Reviewed by AI. π§ What It Does Triggered on PR creation Extracts code diffs from the PR Formats and feeds them into an OpenAI prompt Enriches the prompt using a Google Sheet of Swift best practices Posts an AI-generated review as a comment on the PR Applies a PR label to visually mark reviewed PRs β Prerequisites Before deploying this workflow, ensure you have the following: n8n Instance (Self-hosted or Cloud) GitHub Repository with PR activity OpenAI API Key** for GPT-4o, GPT-4-turbo, or GPT-3.5 GitHub OAuth App** (or PAT) connected to n8n to post comments and access PR diffs (Optional) Google Sheets API credentials if using the code best practices lookup node. βοΈ Setup Instructions 1. Import the Workflow in n8n, click on Workflows β Import from file or JSON Paste or upload the JSON code of this template 2. Configure Triggers and Connections π GitHub Trigger Node**: PR Trigger Repository**: Select the GitHub repo(s) to monitor Events**: Set to pull_request Auth**: Use GitHub OAuth2 credentials π₯ HTTP Request Node: Get file's Diffs from PR No authentication needed; it uses dynamic path from trigger π§ OpenAI Model Node**: OpenAI Chat Model Model**: Select gpt-4o, gpt-4-turbo, or gpt-3.5-turbo Credential**: Provide your OpenAI API Key π§βπ» Code Review Agent Node : Code Review Agent Connected to OpenAI and optionally to tools like Google Sheets π¬ GitHub Comment Poster Uses GitHub API to post review comments back on PR Node: GitHub Robot Credential: Use the agent Github account (OAuth or PAT) Repo : Pick your owen Github Repository π·οΈ PR Labeler (optional) Adds label ReviewedByAI after successful comment Node: Add Label to PR Label : you ca customize the label text of your owen tag. π Google Sheet Best Practices config (optional) Connects to a Google Sheet for coding guideline lookups, we can replace Google sheet by another tool or data base First prepare your best practices list with the clear description and the code bad/good examples Add al the best practices in your Google Sheet Configure* the Code *Best Practices node** in the template : Credential : Use your Google Sheet account by OAuth2 URL : Add your Google Sheet document URL Sheet : Add the name of the best practices sheet
by AlQaisi
Template Information Who is this template for? This template is for users looking to retrieve email information from LinkedIn profiles and update Google Sheets with the collected data. π₯ quick set up video How it works** The template utilizes a series of nodes to fetch email information from LinkedIn profiles. It starts with a Schedule Trigger node that sets the interval for the workflow. The Conditional Check node verifies if certain fields like Name, Gender, Job Title, Summary, and LinkedIn URL are not empty. The HTTP Request node sends a POST request to the specified URL with API key and profile information. The Data Merge node merges the data collected. The Field Editing node modifies the fields as needed. Finally, the Google Sheets Update node updates the Google Sheets with the gathered information. Set Up Instructions Make sure to have the necessary credentials and permissions for accessing LinkedIn and Google Sheets. Set up the API key required for the HTTP Request node. Configure the Google Sheets Update node with the appropriate document ID and sheet name. Check and adjust field mappings in the Field Editing node according to your needs. Run the workflow and monitor the updates in your Google Sheets document. Overview: The workflow is designed to find contact information for LinkedIn profile URLs stored in a Google Sheet. It involves various nodes for different operations such as making HTTP requests, scheduling triggers, reading from and updating Google Sheets, field editing, data merging, and conditional checks. A video demonstrating the workflow process can be accessed here. Copy this template to get started : Google Sheets Using Prospeo.io LinkedIn Email Finder API with cURL To use the API endpoint "https://api.prospeo.io/linkedin-email-finder" with cURL, follow these steps: Use the cURL command with the following parameters: curl -X POST \ -H "Content-Type: application/json" \ -H "X-KEY: your_api_key" \ -d '{ "url": "https://www.linkedin.com/in/john-doe/" }' \ "https://api.prospeo.io/linkedin-email-finder" Replace "your_api_key" with your actual API key. Update the "url" field in the JSON data with the LinkedIn profile URL for which you want to find the email address. To get access to this API and obtain your API key, you need to sign up on the Prospeo platform and subscribe to their LinkedIn email finder service. Once you have subscribed, you will receive an API key that you can use to authenticate your requests to the API endpoint. Description: Schedule Trigger:** Triggers the workflow based on a defined schedule interval, in this case, based on minutes. Schedule Trigger Node Documentation Google Sheets Read:** Reads data from a Google Sheets document and sheet based on the provided document ID and sheet name. Google Sheets Node Documentation Conditional Check:** Checks multiple conditions based on the input data and performs actions accordingly. Conditional Node Documentation HTTP Request:** Sends an HTTP POST request to a specified URL with headers and body parameters. HTTP Request Node Documentation No Operation, do nothing:** Placeholder node that does not perform any operation. Data Merge:** Merges data based on specified mode and combination settings. Merge Node Documentation Field Editing:** Edits fields by setting specific values for each field based on input data. Set Node Documentation Google Sheets Update:** Updates data in a Google Sheets document and sheet based on specified columns and values. Google Sheets Node Documentation
by AlQaisi
Example: @SubAlertMe_Bot Summary: The automated image analysis and response workflow using n8n is a sophisticated solution designed to streamline the process of analyzing images sent via Telegram and delivering insightful responses based on the analysis outcomes. This cutting-edge workflow employs a series of meticulously orchestrated nodes to ensure seamless automation and efficiency in image processing tasks. Use Cases: This advanced workflow caters to a myriad of scenarios where real-time image analysis and response mechanisms are paramount. The use cases include: Providing immediate feedback on images shared within Telegram groups. Enabling automated content moderation based on the analysis of image content. Facilitating rapid categorization and tagging of images based on the results of the analysis. Detailed Workflow Setup: To effectively implement this workflow, users must adhere to a meticulous setup process, which includes: Access to the versatile n8n platform, ensuring seamless workflow orchestration. Integration of a Telegram account to facilitate image reception and communication. Utilization of an OpenAI account for sophisticated image analysis capabilities. Configuration of Telegram and OpenAI credentials within the n8n environment for seamless integration. Proficiency in creating and interconnecting nodes within the n8n workflow for optimal functionality. Detailed Node Description: Get the Image (Telegram Trigger): Actively triggers upon receipt of an image via Telegram, ensuring prompt processing. Extracts essential information from the received image message to initiate further actions. Merge all fields To get data from trigger: Seamlessly amalgamates all relevant data fields extracted from the trigger node for comprehensive data consolidation. Analyze Image (OpenAI): Harnesses the powerful capabilities of OpenAI services to conduct in-depth analysis of the received image. Processes the image data in base64 format to derive meaningful insights from the visual content. Aggregate all fields: Compiles and consolidates all data items for subsequent processing and analysis, ensuring comprehensive data aggregation. Send Content for the Analyzed Image (Telegram): Transmits the analyzed content back to the Telegram chat interface for seamless communication. Delivers the analyzed information in textual format, enhancing user understanding and interaction. Switch Node: The Switch node is pivotal for decision-making based on predefined conditions within the workflow. It evaluates incoming data to determine the existence or absence of specific elements, such as images in this context. Utilizes a set of rules to assess the presence of image data in the message payload and distinguishes between cases where images are detected and when they are not. This crucial node plays a pivotal role in directing the flow of the workflow based on the outcomes of its evaluations. Conclusion: The automation of image analysis processes through this sophisticated workflow not only enhances operational efficiency but also revolutionizes communication dynamics within Telegram interactions. By incorporating this advanced workflow solution, users can optimize their image analysis workflows, bolster communication efficacy, and unlock new levels of automation in image processing tasks.
by Aditya Sharma
Description This intelligent n8n automation streamlines the process of collecting, extracting, and scoring resumes sent to a Gmail inboxβmaking it an ideal solution for recruiters who regularly receive hundreds of applications. The workflow scans incoming emails with attachments, extracts relevant candidate information from resumes using AI, evaluates each candidate based on customizable criteria, and logs their scores alongside contact details in a connected Google Sheet. Who Is This For? Recruiters & Hiring Managers**: Automate the resume screening process and save hours of manual work. HR Teams at Startups & SMBs**: Quickly evaluate talent without needing large HR ops infrastructure. Agencies & Talent Acquisition Firms**: Screen large volumes of resumes efficiently and with consistent criteria. Solo Founders Hiring for Roles**: Use AI to help score and shortlist top candidates from email applications. What Problem Does This Workflow Solve? Manually reviewing resumes is time-consuming, error-prone, and inconsistent. This workflow solves these challenges by: Automatically detecting and extracting resumes from Gmail attachments. Using OpenAI to intelligently extract candidate info from unstructured PDFs. Scoring resumes using customizable evaluation criteria (e.g., relevant experience, skills, education). Logging all candidate data (Name, Email, LinkedIn, Score) in a centralized, filterable Google Sheet. Enabling faster, fairer, and more efficient candidate screening. How It Works 1. Gmail Trigger Runs on a scheduled interval (e.g., every 6 or 24 hours). Scans a connected Gmail inbox (using OAuth credentials) for unread emails that contain PDF attachments. 2. Extract Attachments Downloads the attached resumes from matching emails. 3. Parse Resume Text Sends the PDF file to OpenAI's API (via GPT-4 or GPT-3.5 with file support or via base64 + PDF-to-text tool). Prompts GPT with a structured format to extract fields like Name, Email, LinkedIn, Skills, and Education. 4. Score Resume Evaluates the resume on predefined scoring logic using AI or logic inside the workflow (e.g., "Has X skill = +10 points"). 5. Log to Google Sheets Appends a new row in a connected Google Sheet, including: Candidate Name Email Address LinkedIn URL Resume Score Setup Accounts & API Keys Youβll need accounts and credentials for: n8n** (hosted or self-hosted) Google Cloud Platform** (for Gmail, Drive, and Sheets APIs) OpenAI** (for GPT model access) Google Sheet Make a Google Sheet and connect it via Google Sheets node in n8n. Columns should include: Name Email LinkedIn Score Configuration Google Cloud: Enable Gmail API and Google Sheets API. Set up OAuth 2.0 Credentials in Google Console. Connect n8n Gmail, Drive, and Sheets nodes to these credentials. OpenAI: Generate an API Key. Use the HTTP Request node or official OpenAI node to send prompt requests. n8n Workflow: Add Gmail Trigger. Add extraction logic (e.g., filter PDFs). Add OpenAI prompt for resume parsing and scoring. Connect structured output to a Google Sheets node. Requirements Accounts: n8n** Google** (Gmail, Sheets, Drive, Cloud Console) OpenAI** API Keys & Credentials: OpenAI API Key Google Cloud OAuth Credentials Gmail Access Scopes (for reading attachments) Configured Google Sheet OpenAI usage (after free tier) Google Cloud API usage (if exceeding free quota)
by Batu ΓztΓΌrk
π Transform LinkedIn Post Reactions into Content Ideas with Airtable π Description This workflow helps you to turn your LinkedIn activity into a powerful content ideation engine. It captures your most recent post reactions on LinkedIn automatically, filters them based on recency, and structures the content into Airtableβready for brainstorming, inspiration, or publication planning. βοΈ What It Does Fetches* the latest liked posts from LinkedIn via a public API (rapidapi.com/Real-Time Linkedin Scraper*). Filters** posts to include only those marked as your decided reaction and posted in the last 7 days. Extracts** the post text, author, links and more. Formats** the data into a database-friendly structure. Saves** the output in Airtable for easy tracking, tagging, or team collaboration. π‘ Use Cases Build a content idea vault from posts you admire. Capture inspiration from thought leaders. Identify trends based on what you find insightful. Supercharge your personal brand or newsletter by turning likes into learning. π Prerequisites Before using this template, make sure you have: β A RapidAPI account and access to the linkedin-api8 endpoint. β Your RapidAPI key and the target LinkedIn username. β An Airtable account with a base/table set up. π§° Setup Instructions Clone this template into your n8n instance. Open the Fetch LinkedIn Likes node and enter: Your LinkedIn username. Your RapidAPI key in the headers. Open the Save to Airtable node and: Connect your Airtable account. Link the correct base (Content Hub) and table (Ideas). Set your desired schedule in the Trigger node. Activate the workflow and you're done! π Airtable Setup Create a base called Content Hub and a table named Ideas with the following columns: | Column Name | Type | Required | Notes | |-------------|------------|----------|----------------------------| | Title | Single line text | β | Generated from author info | | Description | Long text | β | Contains post content | | Source | URL | β | Link to the original post | | Type | Single select | β | Value: Linkedin
by Keith Rumjahn
WordPress Post Auto-Categorization Workflow π‘ Click here to read detailed case study πΊ Click here to watch youtube tutorial π― Purpose Automatically categorize WordPress blog posts using AI, saving hours of manual work. This workflow analyzes your post titles and assigns them to predefined categories using artificial intelligence. π What This Workflow Does β’ Connects to your WordPress site β’ Retrieves all uncategorized posts β’ Uses AI to analyze post titles β’ Automatically assigns appropriate category IDs β’ Updates posts with new categories β’ Processes dozens of posts in minutes βοΈ Setup Requirements WordPress site with admin access Predefined categories in WordPress OpenAI API credentials (or your preferred AI provider) n8n with WordPress credentials π οΈ Configuration Steps Add your WordPress categories (manually in WordPress) Note down category IDs Update the AI prompt with your category IDs Configure WordPress credentials in n8n Set up AI API connection π§ Customization Options β’ Modify AI prompts for different categorization criteria β’ Adjust for multiple category assignments β’ Add tag generation functionality β’ Customize for different content types β’ Add additional metadata updates β οΈ Important Notes β’ Backup your WordPress database before running β’ Test with a few posts first β’ Review AI categorization results initially β’ Categories must be created manually first π Bonus Features β’ Can be modified for tag generation β’ Works with scheduled posts β’ Handles bulk processing β’ Maintains categorization consistency Perfect for content managers, bloggers, and website administrators looking to organize their WordPress content efficiently. #n8n #WordPress #ContentManagement #Automation #AI Created by rumjahn
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. π₯ 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 Mirajul Mohin
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. What this workflow does Monitors Google Drive for new driver license image uploads Downloads and processes images using VLM Run AI OCR Extracts key information including license number, name, DOB, and dates Saves structured data to Google Sheets for instant access Setup Prerequisites: Google Drive account, VLM Run API credentials, Google Sheets access, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Google Drive OAuth2 and create license upload folder Add VLM Run API credentials Set up Google Sheets integration for data storage Update folder/sheet IDs in workflow nodes Test with sample license images and activate Perfect for Customer onboarding and identity verification KYC compliance and document processing HR employee verification and record keeping Insurance claim processing and validation Any business requiring license data extraction Key Benefits Asynchronous processing** handles high-resolution images without timeouts Multi-format support** for JPG, PNG, PDF, HEIC, WebP formats Structured data output** ready for databases and integrations Eliminates manual entry** saving hours of data input time High accuracy OCR** with multi-state license support How to customize Extend by adding: Address and additional field extraction Data validation and error checking Integration with CRM or customer databases Email notifications for processing completion Audit trails and compliance reporting Duplicate detection and data deduplication This workflow transforms manual license data entry into an automated, accurate, and compliant process, making identity verification seamless and reliable for your business operations.