Integrate LangChain Summarization Chain in your LLM apps and 422+ apps and services

Who is this for? This workflow is for everyone who wants to have easier access to their Odoo sales data without complex queries. Use Case To have a clear overview of your sales data in Odoo you typically needs to extract data from it manually to analyse it. This workflow uses OpenAI's language models to create an intelligent chatbot that provides conversational access to your Odoo sales opportunity data. How it works Creates a summary of all Odoo sales opportunities using OpenAI Uses that summary as context for the OpenAI chat model Keeps the summary up to date using a schedule trigger Set up steps: Configure the Odoo credentials Configure OpenAI credentials Toggle "Make Chat Publicly Available" from the Chat Trigger node.

Use Case: This n8n workflow automates the process of extracting information from emails. It uses OpenAI to summarize sales emails and adds this information in Odoo. How it works: When an email is received with a certain label, it sends the email to OpenAI for summarization A sales opportunity is created in Odoo with the email subject as title and the email summary as internal note Set up steps: Configure Google Cloud credentials with Gmail access In the Gmail node, choose an email label in the filter section Configure OpenAI credentials Configure Odoo credentials

This n8n workflow takes in a document such as a research paper, marketing or sales deck or company filings, and breaks them down into 3 templates: study guide, briefing doc and timeline. These templates are designed to help a student, associate or clerk quickly summarise, learn and understand the contents to be more productive. Study guide - a short quiz of questions and answered generated by the AI Agent using the contents of the document. Briefing Doc - key information and insights are extracted by the AI into a digestable form. Timeline - key events, durations and people are identified and listed into a simple to understand timeline by the AI How it works A local file trigger watches a local network directory for new documents. New documents are imported into the workflow, its contents extracted and vectorised into a Qdrant vector store to build a mini-knowledgebase. The document then passes through a series of template generating prompts where the AI will perform "research" on the knowledgebase to generate the template contents. Generated study guide, briefing and timeline documents are exported to a designated folder for the user. Requirements Self-hosted version of n8n. Qdrant instance for knowledgebase. Mistral.ai account for embeddings and AI model. Customising your workflow Try adding your own templates or adjusting the existing templates to suit your unique use-case. Anything is quite possible and limited only by your imagination! Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1VV5R2nW-IhVcFP_k8uEks4LsLRZrHSNG/view?usp=sharing

Who is this template for? This workflow template is designed for content creators, researchers, educators, and professionals who need quick, accurate summaries of YouTube videos. It’s ideal for those looking to save time, extract key insights, or repurpose video content into concise formats for reports, studies, or social media. What does it do? The workflow automates the process of summarizing YouTube videos by extracting the transcript, analyzing the content, and generating a concise summary. It leverages AI tools to ensure accuracy and relevance, making it easier to digest lengthy videos in seconds. Why is it useful? This template saves hours of manual effort by automating video summarization, enabling users to focus on analyzing or sharing insights rather than watching entire videos. It’s particularly useful for staying updated with trends, conducting research, or creating content efficiently. How does it work? The workflow integrates with YouTube’s Transcript API powered by Apify Actor to fetch video transcripts, process the text using AI-powered summarization tools, and deliver a clear, concise summary. Setup Instructions You need an Apify account and an API key to connect with the Actor. Follow the steps below: Create a Free Account. Choose the appropriate Actor from the Apify search. Under the Integration tab, click on “Use API endpoints.” Select the API that best suits your needs.

This workflow is ideal for businesses looking to automate their email responses, especially for handling inquiries about company information. It leverages AI to ensure accurate and professional communication. How It Works Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new messages. When a new email arrives, it triggers the workflow. Email Preprocessing: The Markdown node converts the email's HTML content into plain text for easier processing by the AI models. Email Summarization: The Email Summarization Chain node uses an AI model (DeepSeek R1) to generate a concise summary of the email. The summary is limited to 100 words and is written in Italian. Email Classification: The Email Classifier node categorizes the email into predefined categories (e.g., "Company info request"). If the email does not fit any category, it is classified as "other". Email Response Generation: The Write email node uses an AI model (OpenAI) to draft a professional response to the email. The response is based on the email content and is limited to 100 words. The Review email node uses another AI model (DeepSeek) to review and format the drafted response. It ensures the response is professional and formatted in HTML (e.g., using `, , , ` tags where necessary). Email Sending: The Send Email node sends the reviewed and formatted response back to the original sender. Vector Database Integration: The Qdrant Vector Store node retrieves relevant information from a vector database (Qdrant) to assist in generating accurate responses. This is particularly useful for emails classified as "Company info request". The Embeddings OpenAI node generates embeddings for the email content, which are used to query the vector database. Document Vectorization: The workflow includes steps to create and refresh a Qdrant collection (Create collection and Refresh collection nodes). Documents from Google Drive are downloaded (Get folder and Download Files nodes), processed into embeddings (Embeddings OpenAI1 node), and stored in the Qdrant vector store (Qdrant Vector Store1 node). Set Up Steps Configure Email Trigger: Set up the Email Trigger (IMAP) node with the appropriate IMAP credentials to monitor the email inbox. Set Up AI Models: Configure the DeepSeek R1, OpenAI, and DeepSeek nodes with the appropriate API credentials for text summarization, response generation, and review. Set Up Email Classification: Define the categories in the Email Classifier node (e.g., "Company info request", "Other"). Ensure the OpenAI 4-o-mini node is configured to assist in classification. Set Up Vector Database: Configure the Qdrant Vector Store and Qdrant Vector Store1 nodes with the appropriate Qdrant API credentials and collection details. Set up the Embeddings OpenAI and Embeddings OpenAI1 nodes to generate embeddings for the email content and documents. Set Up Document Processing: Configure the Get folder and Download Files nodes to access and download documents from Google Drive. Use the Token Splitter and Default Data Loader nodes to process and split the documents into manageable chunks for vectorization. Set Up Email Sending: Configure the Send Email node with the appropriate SMTP credentials to send responses. Test the Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all steps execute correctly. Verify that emails are summarized, classified, and responded to accurately. Activate the Workflow: Once tested, activate the workflow to automate the process of handling incoming emails. Key Features Automated Email Handling**: Automatically processes incoming emails, summarizes them, and generates professional responses. AI-Powered Classification**: Uses AI to classify emails into relevant categories for targeted responses. Vector Database Integration**: Retrieves relevant information from a vector database to enhance response accuracy. Document Vectorization**: Processes and stores documents from Google Drive in a vector database for quick retrieval. Professional Email Formatting**: Ensures responses are professionally formatted and concise.

How it Works This workflow automates the process of handling job applications by extracting relevant information from submitted CVs, analyzing the candidate's qualifications against a predefined profile, and storing the results in a Google Sheet. Here’s how it operates: Data Collection and Extraction: The workflow begins with a form submission (On form submission node), which triggers the extraction of data from the uploaded CV file using the Extract from File node. Two informationExtractor nodes (Qualifications and Personal Data) are used to parse specific details such as educational background, work history, skills, city, birthdate, and telephone number from the text content of the CV. Processing and Evaluation: A Merge node combines the extracted personal and qualification data into a single output. This merged data is then passed through a Summarization Chain that generates a concise summary of the candidate’s profile. An HR Expert chain evaluates the candidate against a desired profile (Profile Wanted), assigning a score and providing considerations for hiring. Finally, all collected and processed data including the evaluation results are appended to a Google Sheets document via the Google Sheets node for further review or reporting purposes [[9]]. Set Up Steps To replicate this workflow within your own n8n environment, follow these steps: Configuration: Begin by setting up an n8n instance if you haven't already; you can sign up directly on their website or self-host the application. Import the provided JSON configuration into your n8n workspace. Ensure that all necessary credentials (e.g., Google Drive, Google Sheets, OpenAI API keys) are correctly configured under the Credentials section since some nodes require external service integrations like Google APIs and OpenAI for language processing tasks. Customization: Adjust the parameters of each node according to your specific requirements. For example, modify the fields in the formTrigger node to match what kind of information you wish to collect from applicants. Customize the prompts given to AI models in nodes like Qualifications, Summarization Chain, and HR Expert so they align with the type of analyses you want performed on the candidates' profiles. Update the destination settings in the Google Sheets node to point towards your own spreadsheet where you would like the final outputs recorded.

How it Works This workflow is designed to automate the process of handling incoming emails, summarizing their content, generating appropriate responses, and obtaining approval before sending replies. Below are the key operational steps: Email Reception and Summarization: The workflow starts with an Email Trigger (IMAP) node that listens for new emails in a specified inbox. Once an email is received, its HTML content is processed by a Markdown node to convert it into plain text if necessary, followed by an Email Summarization Chain node which uses AI to create a concise summary of the email's content using prompts tailored for this purpose. Response Generation and Approval: A Write email node generates a professional response based on the summarized content, utilizing predefined templates and guidelines such as keeping responses under 100 words and ensuring they're formatted correctly in HTML. Before sending out any automated replies, the system sends these drafts via Gmail for human review and approval through a Gmail node configured with double-approval settings. If approved (Approve?), the finalized email is sent back to the original sender using the Send Email node; otherwise, it loops back for further edits or manual intervention. Set Up Steps To replicate this workflow within your own n8n environment, follow these essential configuration steps: Configuration: Begin by setting up an n8n instance either locally or via cloud services offered directly from their official site. Import the provided JSON configuration file into your workspace, making sure all required credentials like IMAP, SMTP, OpenAI API keys, etc., are properly set up under Credentials section since multiple nodes rely heavily on external integrations for functionalities like reading emails, generating summaries, crafting replies, and managing approvals. Customization: Adjust parameters according to specific business needs, including but not limited to adjusting the conditions used during conditional checks performed by nodes like Approve?. Modify the template messages given to AI models so they align closely with organizational tone & style preferences while maintaining professionalism expected in business communications. Ensure correct mappings between fields when appending data to external systems like Google Sheets or similar platforms where records might need tracking post-interaction completion.

How it Works This workflow automates the handling of incoming emails, summarizes their content, generates appropriate responses using a retrieval-augmented generation (RAG) approach, and obtains approval or suggestions before sending replies. Below is an explanation of its functionality divided into two main sections: Email Handling and Summarization: The process begins with the Email Trigger (IMAP) node which listens for new emails in a specified inbox. Once an email is received, the Markdown node converts its HTML content into plain text if necessary, followed by the Email Summarization Chain that uses AI to create a concise summary of up to 100 words. Response Generation and Approval: A Write email node generates a professional response based on the summarized content, ensuring brevity and professionalism while keeping within the word limit. Before sending out any automated replies, the system sends these drafts via Gmail for human review and approval through the Gmail node configured with free-text response options. If approved, the finalized email is sent back to the original sender using the Send Email node; otherwise, it loops back for further edits or manual intervention. Additionally, there's a Text Classifier node designed to categorize feedback from humans as either "Approved" or "Declined", guiding whether the email should proceed directly to being sent or require additional editing. Set Up Steps To replicate this workflow within your own n8n environment, follow these essential configuration steps: Configuration: Begin by setting up an n8n instance either locally or via cloud services offered directly from their official site. Import the provided JSON configuration file into your workspace, making sure all required credentials such as IMAP, SMTP, OpenAI API keys, etc., are properly set up under Credentials since multiple nodes rely heavily on external integrations for functionalities like reading emails, generating summaries, crafting replies, and managing approvals. Customization: Adjust parameters according to specific business needs, including but not limited to adjusting the conditions used during conditional checks performed by nodes like Approve?. Modify the template messages given to AI models so they align closely with organizational tone & style preferences while maintaining professionalism expected in business communications. Ensure correct mappings between fields when appending data to external systems where records might need tracking post-interaction completion, such as Google Sheets or similar platforms.

Automate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API This workflow automates the collection, analysis, and summarization of Pinterest Pin data to help marketers optimize content strategy. It gathers Pinterest Pin performance data, analyzes trends using an AI agent, and delivers actionable insights to the Marketing Manager via email. This setup is ideal for content creators and marketing teams who need weekly insights on Pinterest trends to refine their content calendar and audience engagement strategy. Prerequisites Before setting up this workflow, ensure you have the following: Pinterest API Access & Developer Account Sign up at Pinterest Developers and obtain API credentials. Ensure you have access to both Organic and Paid Pin data. Airtable Account & API Key Create an account at Airtable and set up a database. Obtain an API key from Account Settings. AI Agent for Trend Analysis An AI-powered agent (such as OpenAI's GPT or a custom ML model) is required to analyze Pinterest trends. Ensure integration with your workflow automation tool (e.g., Zapier, Make, or a custom Python script). Email Automation Setup Configure an SMTP email service (e.g., Gmail, Outlook, SendGrid) to send the summarized results to the Marketing Manager. Step-by-Step Guide to Automating Pinterest Pin Analysis 1. Scheduled Trigger for Data Collection At 8:00 AM (or your preferred time), an automated trigger starts the workflow. Adjust the timing based on your marketing schedule to optimize trend tracking. 2. Fetch Data from Pinterest API Retrieve recent Pinterest Pin performance data, including impressions, clicks, saves, and engagement rate. Ensure both Organic and Paid Ads data are labeled correctly for clarity. 3. Store Data in Airtable Pins are logged and categorized in an Airtable database for further analysis. Sample Airtable Template for Pinterest Pins | Column Name | Description | |---------------|---------------------------------------| | pin_id | Unique identifier for each Pin | | created_at | Timestamp of when the Pin was created | | title | Title of the Pin | | description| Short description of the Pin | | link | URL linking to the Pin | | type | Type of Pin (e.g., organic, ad) | 4. AI Agent Analyzes Pinterest Trends The AI model reviews the latest Pinterest data and identifies: Trending Topics & Keywords** Engagement Patterns** Audience Interests & Behavior Changes** Optimal Posting Times & Formats** 5. Generate Content Suggestions with AI The AI Agent recommends new Pin ideas and content calendar updates to maximize engagement. Suggestions include creative formats, hashtags, and timing adjustments for better performance. 6. Summary & Insights Generated by AI A concise report is created, summarizing Pinterest trends and actionable insights for content strategy. 7. Email Report Sent to the Marketing Manager The summary is emailed to the Marketing Manager to assist with content planning and execution. The report includes: Performance Overview of Recent Pins Trending Content Ideas Best Performing Pin Formats AI-Generated Recommendations This workflow enables marketing teams to automate Pinterest analysis and optimize their content strategy through AI-driven insights. 🚀

Webhook | Paper Summarization Who is this for? This workflow is designed for researchers, students, and professionals who frequently read academic papers and need concise summaries. It is useful for anyone who wants to quickly extract key information from research papers hosted on arXiv. What problem is this workflow solving? Academic papers are often lengthy and complex, making it time-consuming to extract essential insights. This workflow automates the process of retrieving, processing, and summarizing research papers, allowing users to focus on key findings without manually reading the entire paper. What this workflow does This workflow extracts the content of an arXiv research paper, processes its abstract and main sections, and generates a structured summary. It provides a well-organized output containing the Abstract Overview, Introduction, Results, and Conclusion, ensuring that users receive critical information in a concise format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Configure an external trigger using the Webhook node to accept paper IDs. Test the workflow by providing an arXiv paper ID. (Optional) Modify the summarization model or output format according to your preferences. How to customize this workflow to your needs Adjust the HTTPRequest node to fetch papers from other sources beyond arXiv. Modify the Summarization Chain node to refine the summary output. Enhance the Reorganize Paper Summary step by integrating additional language models. Add an email or Slack notification step to receive summaries directly. Workflow Steps Webhook receives a request with an arXiv paper ID. Send an HTTP request using "Request to Paper Page" to fetch the HTML content of the paper. Extract the abstract and sections using "Extract Contents". Split out all sections using "Split out All Sections" to process individual paragraphs. Clean up text using "Remove useless links" to remove unnecessary elements. Summarize extracted content using "Summarization Chain". Aggregate summarized content using "Aggregate summarized content". Reorganize the paper summary into structured sections using "Reorganize Paper Summary". Extract key information using "Content Extractor" to classify data into Abstract Overview, Introduction, Results, and Conclusion. Respond to the webhook with the structured summary. Note: This workflow is designed for use with arXiv research papers but can be adapted to process papers from other sources.

Functionality This workflow automates the handling of incoming emails by summarizing their content, generating appropriate responses, and validating the responses through a "Human-in-the-Loop" system. It integrates with IMAP email services (e.g., Gmail, Outlook) and uses AI models to streamline the email response process. The workflow ensures that all AI-generated responses are reviewed by a human before being sent, maintaining a high level of professionalism and accuracy. This approach is particularly useful for businesses that receive a high volume of emails and need to respond quickly while ensuring quality control. How It Works Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new messages. When a new email arrives, it triggers the workflow. Email Preprocessing: The Markdown node converts the email's HTML content into plain text for easier processing by the AI models. Email Summarization: The Email Summarization Chain node uses an AI model (OpenAI) to generate a concise summary of the email. The summary is limited to 100 words and is written in a professional tone. Email Response Generation: The Write email node uses an AI model (OpenAI) to draft a professional response to the email. The response is based on the email content and is limited to 100 words. Human-in-the-Loop Approval: The Set Email text node prepares the drafted response for approval. The Approve Email node sends the drafted response to a human approver (e.g., an internal email address) for review. The email includes: The original message. The AI-generated response. The Approved? node checks if the response has been approved by the human reviewer. If approved, the workflow proceeds to send the response; otherwise, it stops. Sending the Response: The Send Email node sends the approved response back to the original sender. Key Features Automated Email Summarization**: Summarizes incoming emails to provide a quick overview of the content. AI-Powered Response Generation**: Drafts professional responses to emails using AI. Human-in-the-Loop Approval**: Ensures all AI-generated responses are reviewed and approved by a human before being sent. IMAP Integration**: Works with IMAP email services like Gmail and Outlook. Efficient Email Management**: Reduces the time and effort required to handle incoming emails while maintaining high-quality responses. This workflow is ideal for businesses looking to automate their email response process while maintaining control over the quality of outgoing communications. It leverages AI to handle repetitive tasks and ensures that all responses are reviewed by a human, providing a balance between automation and human oversight.

Use case Manually monitoring Reddit for viable business ideas is time-consuming and inconsistent. This workflow automatically analyzes trending Reddit discussions using AI to surface high-potential opportunities, filter irrelevant content, and generate actionable insights - saving entrepreneurs 10+ hours weekly in market research. What this workflow does This AI-powered workflow automatically collects trending Reddit discussions, analyzes posts for viable business opportunities using GPT-4, applies smart filters to exclude low-value content, and generates scored opportunity reports with market insights. It identifies unmet customer needs through sentiment analysis, prioritizes high-potential ideas using custom criteria, and outputs structured data to Google Sheets for actionable decision-making. Setup Add Reddit,Google and OpenAI credentials Configure target subreddits in Subreddit node Test workflow by testing workflow Review generated opportunity report in Google Sheets How to adjust this template Change data sources**: Replace Reddit trigger with Twitter/X or Hacker News API Modify criteria**: Adjust scoring thresholds in Opportunity Calculator node Add integrations**: Create automatic Slack alerts for urgent opportunities Generate draft business plans using AI Document Writer

This workflow automates document summarization directly from Google Drive, processes the content using Mistral AI, and delivers a clean, styled summary via Gmail. It's ideal for professionals who need quick insights from lengthy documents without manually reading through them. ✅ Key Features: Google Drive Integration: Fetches a file (PDF/DOCX) from your Drive. AI Summarization: Uses Mistral AI to extract key points efficiently. Styled Email Output: Delivers a formatted, easy-to-read summary to your inbox with a timestamp. Error Handling: Built to skip corrupted files or missing credentials. 🔧 Nodes Breakdown: 1️⃣ Manual Trigger — Starts the workflow manually for easy testing. 2️⃣ Google Drive Node — Downloads a specified file from Google Drive (supports PDF/DOCX). 3️⃣ Mistral Cloud Chat Model Node — Connects to Mistral AI for summarization. 4️⃣ Summarization Chain Node — Breaks the file into chunks, processes content, and generates a concise summary. 5️⃣ Gmail Node — Sends the styled summary directly to the user’s inbox, with custom formatting and current time in the Lagos timezone. Extra Features: Dynamic Time Formatting: Supports Lagos timezone (easily adjustable). HTML Styling: Beautiful email formatting with headers, icons, and line breaks for clarity. Custom Email Sender Name: Branded output (e.g., "Swot.AI"). Future Expansion: Can extend to WhatsApp or Slack with minor tweaks. Use Cases: Legal teams summarizing contracts. Content creators extracting highlights from research papers. Business analysts getting insights from reports on-the-go. Customization Tips: Change the timezone (Africa/Lagos) to match your preferred location. Add error-handling nodes for missing files or API failures. Swap Mistral AI with OpenAI for different summarization behavior. Why To Use This Workflow? This automation saves hours of manual reading. It’s perfect for personal productivity, legal analysis, content creation, or business reporting. With clean formatting and a professional email summary — your team will get instant insights in seconds!

Real Estate Price-Reduced Property Opportunity Guide Overview This comprehensive automation solution targets FSBO properties listed on Zillow that have recently had their price reduced, providing both investment analysis and tailored outreach scripts. The workflow gathers comprehensive market data to analyze local trends for each specific city and incorporates this intelligence into personalized communication strategies (more aggressive in buyers' markets, more value-focused in sellers' markets). Key benefits: Identify motivated homeowners who have recently reduced their property prices Prepare data-driven offer strategies based on detailed market conditions Develop effective, personalized communication approaches Create a consistent, automated workflow to find and capitalize on opportunities Requirements Airtable account (free tier works) n8n automation platform OpenAI API key Zillow Rapid API access Basic understanding of automation workflows Step 1: Set Up Airtable Database Create a new Airtable base Set up a table with the following fields: Property ID (primary field) Address Price Status (single select field with options: "Contacted" and "Uncontacted") Phone Number Communication Template Market Analysis Offer Price Investment Metrics (Long text field for detailed financial analysis) Expected Cash Flow (Currency field) Expected ROI (Percentage field) Follow-up Date Set the default Status to "Uncontacted" Generate a Personal Access Token from Airtable settings for API connections Step 2: Configure Zillow API Connection Set up an HTTP request node in n8n to connect to Zillow's Rapid API Configure the search parameters: Listing type: "For Sale By Owner" Location: Your target market Price reduction: true Auction properties: false Add filters to: Exclude properties without contact information Only include listings with recent price reductions Filter by minimum square footage or bedrooms if desired Set maximum days since price reduction (e.g., last 14 days) Step 3: Market Analysis Workflow Our market analysis engine processes Zillow market data to provide strategic insights for each location: Comprehensive Market Indicators**: Current inventory levels and new listing rates Median list price and sale price comparison Days-to-pending metrics (current and historical) Sale-to-list price ratios Percentage of properties selling above/below list price Market Trend Analysis**: 6-month and year-over-year comparative trends Market trend scoring system (-10 to +10 scale) Market cycle position identification (Early, Mid, Late) Seasonal market pattern recognition Strategic Investment Guidance**: Market type classification (Buyer's, Balanced, Seller's) Negotiation power assessment Market timing recommendations Risk evaluation (Low to High scale) Actionable investment strategies based on current conditions This analysis is transformed into actionable advice that directs your negotiation approach and helps you calibrate offers appropriately for market conditions. Step 4: Calculate Investment Metrics Our investment calculator analyzes each Zillow property and its RentZestimate to provide comprehensive financial projections: Purchase & Financing Analysis**: Purchase price and standard acquisition costs (20% down payment, 3% closing costs) Loan amount and monthly mortgage payment (30-year term) Total initial investment calculation Monthly Expense Projections**: Property tax (2% of property value annually) Insurance (0.5% of property value annually) Maintenance reserves (1% of property value annually) Vacancy allowance (8% of rental income) Total monthly expense calculation Rental Income & Returns**: RentZestimate integration (with 1% rule fallback when unavailable) Monthly and annual cash flow projections Cash-on-cash ROI calculation Break-even timeline analysis Investment Quality Filtering**: Automatic filtering to show only positive cash flow properties Property identification with complete details (address, beds, baths, sqft) Full investment metrics breakdown for investor decision-making This calculator ensures you focus only on properties with profit potential, saving you countless hours of manual analysis. Step 5: Generate Communication Templates Create templates that combine: Property details (address, price, features) Market intelligence from your analysis Investment metrics showing the property's potential Configures your templates to include: A professional introduction Reference to the specific property address Mention of the price reduction A strategic cash offer (typically 5-15% below asking) Local market statistics to build credibility A clear call to action (request to visit the property) Step 6: Automated Workflow Set up the complete n8n workflow to: Check for new listings with price reductions daily Run market analysis on each new property Calculate potential investment returns Generate personalized communication templates Upload data to Airtable Flag properties ready for contact Update status to "Contacted" after outreach Troubleshooting If outreach isn't being tracked: Check API connections to Airtable If market data seems incorrect: Verify Zillow API parameters and location settings If offers are too low/high: Adjust your calculation parameters Step by Step tutorial: https://youtu.be/IqVw9CIL254?si=MKE5UY4rD0TOMLPg By following this guide, you'll have a functional system that can identify opportunities, analyze market conditions, and help you create personalized offers to potential sellers—all while minimizing the manual effort required so you can focus on closing deals.

This workflow automates the process of analyzing emails and their attachments (PDFs and images) using AI models (DeepSeek, Gemini, and OpenRouter). It extracts and summarizes the content of emails and attachments, saves the summaries to Google Sheets, and sends a final consolidated summary via Telegram. This is a powerful tool for automating email analysis and summarization, saving time and ensuring that important information is easily accessible and actionable. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to process incoming emails, analyze their content and attachments, and generate summaries. Here's how it works: Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new emails. If an email contains attachments, the workflow processes them. Check for Attachments: The Contain Attachments? node checks if the email has attachments. If attachments are present, the workflow proceeds to process them. Process Attachments: The Get PDF and Images Attachments node extracts PDF and image attachments from the email. The Switch node separates PDFs and images for further processing: PDFs: The Extract from PDF node extracts text from PDFs, and the PDF Analyzer node summarizes the content. Images: The Analyze Image node uses AI to describe the content of images. Summarize Email Content: The Convert Text node converts the email's HTML content to plain text. The Email Summarization Chain node uses AI to generate a summary of the email's text content. Save Summaries: The Save Summary PDF, Save Summary Image, and Save Summary Text nodes save the summaries of PDFs, images, and email text, respectively, to Google Sheets. Consolidate Summaries: The All Summaries node aggregates the summaries of the email text, PDFs, and images. The Create Final Summary node uses AI to generate a unified summary of all the content. Send Final Summary: The Send Final Summary node sends the consolidated summary via Telegram to a specified chat ID. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: IMAP Configuration: Set up IMAP credentials in n8n for the Email Trigger (IMAP) node. Ensure the email account is accessible via IMAP. AI Model Configuration: Configure the DeepSeek, Gemini, and OpenRouter credentials in n8n for the Email Summarization Chain, PDF Analyzer, and Create Final Summary nodes. Ensure the AI models are set up to generate summaries. Google Sheets Integration: Set up Google Sheets credentials in n8n for the Save Summary PDF, Save Summary Image, and Save Summary Text nodes. Specify the Google Sheet and worksheet where the summaries will be saved. Telegram Integration: Set up Telegram credentials in n8n for the Send Final Summary node. Insert your Chat ID in the Telegram node to receive the final summary. Test the Workflow: Send an email with attachments (PDFs and images) to the monitored email account. The workflow will: Extract and summarize the email content and attachments. Save the summaries to Google Sheets. Send a consolidated summary via Telegram. Optional Customization: replace IMAP trigger with Gmail or Outlook trigger Modify the workflow to include additional features, such as: Adding more AI models for different types of analysis. Sending notifications via other channels (e.g., Slack, email). Integrating with other storage services (e.g., Dropbox, AWS S3).