AI-powered RAG workflow for stock earnings report analysis
This n8n workflow creates a financial analysis tool that generates reports on a company's quarterly earnings using the capabilities of OpenAI GPT-4o-mini, Google's Gemini AI and Pinecone's vector search. By analyzing PDFs of any company's earnings reports from their Investor Relations page, this workflow can answer complex financial questions and automatically compile findings into a structured Google Doc. How it works: Data loading and indexing Fetches links to PDF earnings document from a Google Sheet containing a list of file links. Downloads the PDFs from Google Drive. Parses the PDFs, splits the text into chunks, and generates embeddings using the Embeddings Google AI node (text-embedding-004 model). Stores the embeddings and corresponding text chunks in a Pinecone vector database for semantic search. Report generation with AI agent Utilizes an AI Agent node with a specifically crafted system prompt. The agent orchestrates the entire process. The agent uses a Vector Store Tool to access and retrieve information from the Pinecone database. Report delivery Saves the generated report as a Google Doc in a specified Google Drive location. Set up steps Google Cloud Project & Vertex AI API: Create a Google Cloud project. Enable the Vertex AI API for your project. Google AI API key: Obtain a Google AI API key from Google AI Studio. Pinecone account and API key: Create a free account on the Pinecone website. Obtain your API key from your Pinecone dashboard. Create an index named company-earnings in your Pinecone project. Google Drive - download and save financial documents: Go to a company you want to analize and download their quarterly earnings PDFs Save the PDFs in Google Drive Create a Google Sheet that stores a list of file URLs pointing to the PDFs you downloaded and saved to Google Drive Configure credentials in your n8n environment for: Google Sheets OAuth2 Google Drive OAuth2 Google Docs OAuth2 Google Gemini(PaLM) Api (using your Google AI API key) Pinecone API (using your Pinecone API key) Import and configure the workflow: Import this workflow into your n8n instance. Update the List Of Files To Load (Google Sheets) node to point to your Google Sheet. Update the Download File From Google Drive to point to the column where the file URLs are Update the Save Report to Google Docs node to point to your Google Doc where you want the report saved.
By Mihai FarcasReusable subworkflow zip multiple files dynamically (compress)
📦 Zip Multiple Files Dynamically This template enables you to dynamically bundle multiple files into a ZIP archive. Designed to be used as a Subworkflow, it’s modular, flexible, and easy to integrate into various workflows. The output is a single ZIP file with a name that includes the current date, time, and fileName. Shoutout: Code from: Tom (mutedjam) --- 👤 Who is this for? This workflow is perfect for: 🚀 Businesses automating file archiving tasks. 💻 Developers managing files programmatically. 📂 Anyone needing a reusable solution for bundling files into ZIP archives. --- ❓ What problem is this workflow solving? Manually zipping multiple files is: 🕒 Time-consuming. 🤔 Prone to errors. This workflow automates the process and, as a Subworkflow, ensures: ⚡ Consistent file archiving across different workflows. 🛠️ Reduced manual effort. 📈 Streamlined integration into existing automation. --- 🔧 What this workflow does 🗂️ Dynamically collects binary files from the input. 📦 Bundles them into a single ZIP archive. 🕒 Names the ZIP file with the current date, time, and a customizable fileName. ✅ Outputs the ZIP file, ready for storage or further processing. --- ⚙️ Setup 🔗 Add this Subworkflow to your existing workflows. 📥 Pass the binary files as input to the Subworkflow. ▶️ Call the Subworkflow to generate a ZIP file. --- 🛠️ How to customize this workflow to your needs 🌐 File Sources: Adjust the input nodes in your parent workflow to connect to your preferred file sources. 📝 File Naming: Customize the logic for the output fileName in the Subworkflow. 🚀 Additional Use Cases: Use this Subworkflow in various scenarios, such as: ✉️ Sending ZIP files via email. ☁️ Uploading ZIP files to cloud storage. 🔄 Triggering further automation. --- 🎉 Why use this as a Subworkflow? Instead of building a fixed ZIP functionality for every workflow, this template offers a reusable solution that can be integrated into many different workflows effortlessly. Save time and ensure consistency across your automation projects! 💡
By SimonAutomatically collect & process Google News articles to Google Sheets
Overview This workflow automatically collects the latest articles from Google News RSS feeds, cleans and deduplicates them, and stores them neatly in a Google Sheet. It runs on a set schedule (every Monday at 09:00 by default) and helps you build a fresh pool of content ideas for newsletters, blogs, or social media. --- What you can do with it 🔎 Research faster – pull in fresh articles from multiple RSS sources without manual searching. 🧼 Clean & normalize – extract the real article URL (instead of Google redirects), keep only the title, summary, and date. 🗑 No duplicates – filter out empty or repeated entries before they ever reach your sheet. 📊 Central storage – append all new, unique links into a Google Sheet for review or further automation. --- How it works Trigger – Cron starts the flow every Monday at 09:00 (you can change the schedule). RSS Read – Fetches articles from multiple Google News queries (e.g., “AI”, “AI Automation”). Merge – Combines all feed results into one list. Set (Clean URL) – Extracts the real URL, title, summary, and publication date. Filter – Ensures only items with a valid title and URL continue. Unique by URL – Removes duplicate articles across feeds. Google Sheets Append – Saves new links into your chosen Sheet for review and later use. --- Setup Instructions Import workflow into your n8n instance. Update RSS feeds: Replace the example Google News RSS URLs (AI, AI Automation) with your own queries. Format: https://news.google.com/rss/search?q=YOUR_QUERY&hl=de&gl=DE&ceid=DE:de Connect Google Sheets: Add your Google Sheets credentials. Select the documentId (the spreadsheet) and sheetName (the tab) in the Append new Links node. Recommended columns: date, title, url, summary. Adjust schedule: In the Trigger: Montag 09:00 node, change the cron expression to daily or multiple times per day if you want. Run test: Execute once manually. Check your sheet for the first rows. --- Tips & Extensions ✅ Add more RSS Read nodes for additional sources (blogs, media outlets, niche topics). ✅ Chain this workflow with an AI node (OpenAI/GPT) to automatically generate post ideas from the collected articles. ✅ Notify yourself in Slack/Telegram when new articles are added. ✅ Use a status column (Draft, Approved, Posted) to manage a simple content pipeline directly from the sheet. --- 👉 With this template you’ll never run out of content ideas – everything flows into one place, ready to inspire your next posts, newsletters, or campaigns.
By SuSSmart Amazon shopping assistant with Gemini AI and Telegram
🛒 Smart Telegram Shopping Assistant with AI Product Recommendations Workflow Overview Target User Role: E-commerce Business Owners, Affiliate Marketers, Customer Support Teams Problem Solved: Businesses need an automated way to help customers find products on Telegram without manual intervention, while providing intelligent recommendations that increase conversion rates. Opportunity Created: Transform any Telegram channel into a smart shopping assistant that can handle both product queries and customer conversations automatically. --- What This Workflow Does This workflow creates an intelligent Telegram bot that: 🤖 Automatically detects whether users are asking about products or just chatting 🛒 Scrapes Amazon in real-time to find the best matching products 🎯 Uses AI to analyze and rank products based on price, ratings, and user needs 📱 Delivers perfectly formatted recommendations optimized for Telegram 💬 Handles casual conversations professionally when users aren't shopping Real-World Use Cases E-commerce Support: Reduce customer service workload by 70% Affiliate Marketing: Automatically recommend products with tracking links Telegram Communities: Add shopping capabilities to existing channels Product Discovery: Help customers find products they didn't know existed --- Key Features & Benefits 🧠 Intelligent Intent Detection Uses Google Gemini AI to understand user messages Automatically routes to product search or conversation mode Handles multiple languages and casual typing styles 🛒 Real-Time Product Data Integrates with Apify's Amazon scraper for live data Fetches prices, ratings, reviews, and product details Processes up to 10 products per search instantly 🎯 AI-Powered Recommendations Analyzes multiple products simultaneously Ranks by relevance, value, and user satisfaction Provides top 5 personalized recommendations with reasoning 📱 Telegram-Optimized Output Perfect formatting with emojis and markdown Respects character limits for mobile viewing Includes direct purchase links for easy buying --- Setup Requirements Required Credentials Telegram Bot Token - Free from @BotFather Google Gemini API Key - Free tier available at AI Studio Apify API Token - Free tier includes 100 requests/month Required n8n Nodes @n8n/n8n-nodes-langchain (for AI functionality) Built-in Telegram, HTTP Request, and Code nodes --- Quick Setup Guide Step 1: Telegram Bot Creation Message @BotFather on Telegram Create new bot with /newbot command Copy the bot token to your credentials Step 2: AI Configuration Sign up for Google AI Studio Generate API key for Gemini Add credentials to all three AI model nodes Step 3: Product Scraping Setup Register for free Apify account Get API token from dashboard Add token to "Amazon Product Scraper" node Step 4: Activation Import workflow JSON Add your credentials Activate the Telegram Trigger Test with a product query! --- Workflow Architecture 📱 Message Entry Point Telegram Trigger receives all messages 🧹 Query Preprocessing Cleans and normalizes user input for better search results 🤖 AI Intent Classification Determines if message is product-related or conversational 🔀 Smart Routing Directs to appropriate workflow path based on intent 💬 Conversation Path Handles greetings, questions, and general support 🛒 Product Search Path Scrapes Amazon → Processes data → AI analysis → Recommendations 📤 Optimized Delivery Formats and sends responses back to Telegram --- Customization Opportunities Easy Modifications Multiple Marketplaces: Add eBay, Flipkart, or local stores Product Categories: Specialize for electronics, fashion, etc. Language Support: Translate for different markets Branding: Customize responses with your brand voice Advanced Extensions Price Monitoring: Set up alerts for price drops User Preferences: Remember customer preferences Analytics Dashboard: Track popular products and queries Affiliate Integration: Add commission tracking links --- Success Metrics & ROI Performance Benchmarks Response Time: 3-5 seconds for product queries Accuracy: 90%+ relevant product matches User Satisfaction: 85%+ positive feedback in testing Business Impact Reduced Support Costs: Automate 70% of product inquiries Increased Conversions: Personalized recommendations boost sales 24/7 Availability: Never miss a customer inquiry Scalability: Handle unlimited concurrent users --- Workflow Complexity Intermediate Level - Requires API setup but includes detailed instructions. Perfect for users with basic n8n experience who want to create something powerful.
By Roshan RamaniCreate images from text prompts using Flux Kontext Pro and Replicate
This workflow provides automated access to the Black Forest Labs Flux Kontext Pro AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for image generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete image generation process using the Black Forest Labs Flux Kontext Pro model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: A state-of-the-art text-based image editing model that delivers high-quality outputs with excellent prompt following and consistent results for transforming images through natural language Key Capabilities High-quality image generation from text prompts Advanced AI-powered visual content creation Customizable image parameters and styles Tools Used n8n: The automation platform that orchestrates the workflow Replicate API: Access to the Black Forest Labs/flux-kontext-pro AI model Black Forest Labs Flux Kontext Pro: The core AI model for image generation Built-in Error Handling: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Image Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Creation: Generate unique images for blogs, social media, and marketing materials Design Prototyping: Create visual concepts and mockups for design projects Art & Creativity: Produce artistic images for personal or commercial use Marketing Materials: Generate eye-catching visuals for campaigns and advertisements Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Replicate API: https://replicate.com (Sign up to access powerful AI models) n8n automation ai replicate aiautomation workflow nocode imagegeneration aiart texttoimage visualcontent aiimages generativeart flux machinelearning artificialintelligence aitools automation digitalart contentcreation productivity innovation
By Yaron BeenAnalyze & summarize Amazon product reviews with Decodo, OpenAI and Google Sheets
Disclaimer Please note - This workflow is only available on n8n self-hosted as it’s making use of the community node for the Decodo Web Scraping This n8n workflow automates the process of scraping, analyzing, and summarizing Amazon product reviews using Decodo’s Amazon Scraper, OpenAI GPT-4.1-mini, and Google Sheets for seamless reporting. It turns messy, unstructured customer feedback into actionable product insights — all without manual review reading. Who this is for This workflow is designed for: E-commerce product managers who need consolidated insights from hundreds of reviews. Brand analysts and marketing teams performing sentiment or trend tracking. AI and data engineers building automated review intelligence pipelines. Sellers and D2C founders who want to monitor customer satisfaction and pain points. Product researchers performing market comparison or competitive analysis. What problem this workflow solves Reading and analyzing hundreds or thousands of Amazon reviews manually is inefficient and subjective. This workflow automates the entire process — from data collection to AI summarization — enabling teams to instantly identify customer pain points, trends, and strengths. Specifically, it: Eliminates manual review extraction from product pages. Generates comprehensive and abstract summaries using GPT-4.1-mini. Centralizes structured insights into Google Sheets for visualization or sharing. Helps track product sentiment and emerging issues over time. What this workflow does Here’s a breakdown of the automation process: Set Input Fields Define your Amazon product URL, geo region, and desired file name. Decodo Amazon Scraper Fetches real-time product reviews from the Amazon product page, including star ratings and AI-generated summaries. Extract Reviews Node Extracts raw customer reviews and Decodo’s AI summary into a structured JSON format. Perform Review Analysis (GPT-4.1-mini) Uses OpenAI GPT-4.1-mini to create two key summaries: Comprehensive Review: A detailed summary that captures sentiment, recurring themes, and product pros/cons. Abstract Review: A concise executive summary that captures the overall essence of user feedback. Persist Structured JSON Saves the raw and AI-enriched data to a local file for reference. Append to Google Sheets Uploads both the original reviews and AI summaries into a Google Sheet for ongoing analysis, reporting, or dashboard integration. Outcome: You get a structured, AI-enriched dataset of Amazon product reviews — summarized, searchable, and easy to visualize. Setup Pre-requisite If you are new to Decode, please signup on this link visit.decodo.com Please make sure to install the n8n custom node for Decodo. Step 1 — Import the Workflow Open n8n and import the JSON workflow template. Ensure the following credentials are configured: Decodo Credentials account → Decodo API Key OpenAI account → OpenAI API Key Google Sheets account → Connected via OAuth Step 2 — Input Product Details In the Set node, replace: amazon_url → your product link (e.g., https://www.amazon.com/dp/B0BVM1PSYN) geo → your region (e.g., US, India) file_name → output file name (optional) Step 3 — Connect Google Sheets Link your desired Google Sheet for data storage. Ensure the sheet columns match: product_reviews all_reviews Step 4 — Run the Workflow Click Execute Workflow. Within seconds, your Amazon product reviews will be fetched, summarized by AI, and logged into Google Sheets. How to customize this workflow You can tailor this workflow for different use cases: Add Sentiment Analysis — Add another GPT node to classify reviews as positive, neutral, or negative. Multi-Language Reviews — Include a language detection node before summarization. Send Alerts — Add a Slack or Gmail node to notify when negative sentiment exceeds a threshold. Store in Database — Replace Google Sheets with MySQL, Postgres, or Notion nodes. Visualization Layer — Connect your Google Sheet to Looker Studio or Power BI for dynamic dashboards. Alternative AI Models — Swap GPT-4.1-mini with Gemini 1.5 Pro, Claude 3, or Mistral for experimentation. Summary This workflow transforms the tedious process of reading hundreds of Amazon reviews into a streamlined AI-powered insight engine. By combining Decodo’s scraping precision, OpenAI’s summarization power, and Google Sheets’ accessibility, it enables continuous review monitoring. In one click, it delivers comprehensive and abstract AI summaries, ready for your next product decision meeting or market strategy session.
By Ranjan DailataProduct review analysis with BrowserAct & Gemini-powered recommendations
Product Review Analysis with BrowserAct & Gemini-Powered Recommendations. This n8n template demonstrates how to perform product review sentiment analysis and generate improvement recommendations using an AI Agent. This workflow is perfect for e-commerce store owners, product managers, or marketing teams who want to automate the process of collecting feedback and turning it into actionable insights. --- How it works The workflow is triggered manually. An HTTP Request node initiates a web scraping task with the BrowserAct API to collect product reviews. A series of If and Wait nodes are used to check the status of the scraping task. If the task is not yet complete, the workflow pauses and retries until it receives the full dataset. An AI Agent node, powered by Google Gemini, then processes the scraped review summaries. It analyzes the sentiment of each review and generates actionable improvement recommendations. Finally, the workflow sends these detailed recommendations via a Telegram message and an Email to the relevant stakeholders. --- Requirements BrowserAct API account for web scraping BrowserAct "Product Review Sentiment Analysis" Template Gemini account for the AI Agent Telegram and SMTP credentials for sending messages --- Need Help ? How to Find Your BrowseAct API Key & Workflow ID How to Connect n8n to Browseract How to Use & Customize BrowserAct Templates --- Workflow Guidance and Showcase How to INSTANTLY Get Product Improvement Ideas from Amazon Reviews | BrowserAct + n8n + Gemini
By Madame AI Team | KaiAutomate social media content planning with Llama 3.3 AI, trending topics & Google Suite
How it works: Daily Trigger: Every morning at 8 AM, the workflow is automatically triggered. Fetch Trending Topics: The workflow collects trending topics from external sources, such as news RSS feeds and Reddit popular posts. These trends are merged and summarized to provide up-to-date context for content generation. Read Active Campaigns: The workflow reads all rows from the “Active Campaigns” Google Sheet, but only processes campaigns with a status of "active" to avoid generating content for paused or inactive campaigns. Enrich Campaigns with Trends: Each active campaign is enriched with the latest trending topics, so the generated content can reference current events or popular themes. AI Content Generation: For each enriched campaign, Groq AI generates: An engaging post caption tailored to the platform and target audience Creative direction with visual suggestions Relevant hashtags (5-10) Best posting time recommendation for the platform Quality Scoring: The workflow calculates a quality score for each generated content idea, considering factors like caption length, hashtag count, and creative direction. Append to Google Sheets: The generated content ideas, along with their quality scores and other details, are appended to the “Daily Content Plan” Google Sheet for record-keeping and team collaboration. Schedule in Google Calendar: For each campaign, an event is created in Google Calendar with the content details and recommended posting time, ensuring the team is reminded to review or publish the content. Daily Email Summary (Optional): At the end of the process, a summary email can be sent to the team, including statistics such as the number of campaigns processed, average quality score, and a platform breakdown. Set up steps: Prepare Your Google Sheets: Create a sheet named “Active Campaigns” with columns: Project Name, Theme, Target Audience, Platform, and Status (to mark campaigns as active/inactive). Create another sheet named “Daily Content Plan” with columns for Project Name, Date, Platform, Caption, Creative Direction, Hashtags, and any other details you want to track. Connect Google Services to n8n: In n8n, set up and authenticate your Google Sheets and Google Calendar credentials. You can find authentication information in the n8n documentation for Google credentials. Add a Cron Node: Drag in a Cron node and set it to trigger every day at 8:00 AM. Read Campaigns from Google Sheets: Add a Google Sheets node. Set the operation to “Read Rows” and select your “Active Campaigns” sheet. (Optional) Use a Filter or IF node to process only rows where Status is “active”. (Optional) Fetch Trending Topics: If you want to enrich your content with trending topics, add nodes to fetch data from RSS feeds, Reddit, or other sources. Process Each Campaign: Use a SplitInBatches node to process each campaign row individually. Generate Content Ideas with Groq AI: Add a Groq AI node (or OpenAI node if Groq is not available). Configure the prompt to generate a content idea using the campaign’s theme, target audience, and platform. You can reference fields from the Google Sheets node using expressions like $("Google Sheets").item.json['Theme']. Append Results to “Daily Content Plan”: Add another Google Sheets node. Set the operation to “Append” and select your “Daily Content Plan” sheet. Map the generated content fields to the appropriate columns. Schedule Events in Google Calendar: Add a Google Calendar node. Set the operation to “Create Event”. Use the project name and content idea for the event title and description, and set the event time as needed. (Optional) Send a Daily Summary Email: Add an Email node to send a summary of the day’s content plan to your team. Test the Workflow: Run the workflow manually to ensure all steps work as expected. Check that new content ideas appear in the “Daily Content Plan” sheet and that events are created in Google Calendar. Activate the Workflow: Once you’ve confirmed everything works, activate the workflow so it runs automatically every morning.
By DigiMetaLab