AI Automation Workflows — Page 34 | Neura Market
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    Artificial Intelligence tools and workflows

    • Automate AI Grant Scraping and Eligibility Assessment

      This n8n workflow automates the process of scraping AI grants from grants.gov, assesses their eligibility using AI, and sends email alerts for relevant opportunities.

      n8nFree

    • AI-Powered MIS Agent

      The AI-powered MIS Agent is an intelligent, automated system built using n8n that streamlines email-based data collection and document organization for businesses. It classifies incoming emails, extracts and processes attachments or Drive links, and routes them to the correct destination folders in Google Drive. Additionally, it provides advanced file operations like cleaning, merging, joining, and transforming data. ### Advantages - **Automated Email and File Management** Detects and processes emails containing attachments or Drive links, ensuring seamless classification and routing of business-critical files. - **AI-Based Classification** Uses LLMs (like GPT-4 Mini) to classify emails into categories such as Daily Sales, Customer Info, and Address based on their content. - **Smart File Routing and Upload** Recognizes whether a file is a direct attachment or a Google Drive link, extracts the file ID if necessary, and uploads it to predefined folders. - **Powerful Data Operations** Supports operations like append, join, group by, aggregation, and standardization of data directly from spreadsheets using Python and Pandas within the workflow. - **Scheduled and Triggered Automation** Supports scheduled runs and real-time email triggers, making it highly reliable and timely. - **Fully Modular and Scalable** Easily expandable with more logic, new folders, or different workflows. Clean architecture and annotations make maintenance simple. ### How It Works #### Email Trigger The system uses a Gmail trigger to monitor incoming emails with specific labels or attachments. #### Classification An LLM-based text classifier identifies the purpose of the email (e.g., sales data, address list, customer details). #### Conditional Logic Regex-based conditions check if the email contains Google Drive links or attachments. #### File Handling If it's a Drive link, it extracts the file ID and copies it to the correct folder. If it's an attachment, it uploads directly. #### Scheduled Data Management Periodically moves or logs files from predefined folders using a schedule trigger. #### Data Cleaning and Processing Performs data cleaning and transformation tasks like replacing missing values, standardizing formats, and joining datasets based on criteria provided by the user. #### Final Output Cleaned and processed files are saved in designated folders with their public links shared back through the system. ### Set Up Steps Configure Nodes: - Gmail Trigger: Detects relevant incoming emails. - Text Classifier: Uses OpenAI model to categorize email content. - Regex Conditions: Determine whether a link or attachment is present. - Google Drive Operations: Upload or copy files to categorized folders. - Python Nodes: Handle data manipulation using Pandas. - Google Sheets Nodes: Extract, clean, and write structured data. - LLM-based Chat Models: Extract and apply cleaning configurations. ### Connect Nodes: - Seamlessly connect Gmail inputs, classification, file processing, and data logic. - Output links or processed files are uploaded back to Drive and ready to share. ### Credentials: Ensure OAuth credentials for Gmail, Google Drive, and OpenAI are correctly set. ### Ideal For - Sales & CRM teams managing large volumes of email-based reports. - Data teams needing structured pipelines from unstructured email inputs. - Businesses looking to automate classification, storage, and transformation of routine data. ### Testing and Additional Customization - If you want to test this bot's capability before purchasing the workflow, ask me on my mail kumar.shivam19oce@gmail.com. I will share the chat URL and the links of associated Google Drives to see the result. Once you are satisfied, then we are good to go. I have just kept $1 for testing purposes because of paid OpenAI. - If there is any customization needed like charts and other requests like adding databases, feel free to let me know; I can do it accordingly. This is the first version; I will come with more advancements based on the request and responses. ### Use it and let me know on kumar.shivam19oce@gmail.com

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  1. AI-Driven Slack Chatbot with Contextual Memory and Information Retrieval

    Leverage AI to create an interactive Slack chatbot that uses contextual memory and external information sources for enhanced responses. This workflow integrates AI models and information retrieval tools to deliver a dynamic chatbot experience.

    n8nFree

  2. Automate Driver License Data Extraction with Google Drive, VLM Run, and Google Sheets

    Streamline the process of extracting data from driver license images uploaded to Google Drive using VLM Run's AI OCR, and store the structured data in Google Sheets.

    n8nFree

  3. Automate Business Prospect Searches with Natural Language Queries

    This n8n workflow enables users to find business prospects using natural language queries, leveraging Claude AI for interpretation and Explorium MCP for data retrieval. Results are exported as a CSV file, simplifying the process for sales and business development teams.

    n8nFree

  4. Convert Images to 3D Models with Faller AI and Store in Google Drive

    This workflow allows users to **convert a 2D image into a 3D model** by integrating multiple AI and web services. The process begins with a user uploading or providing an image URL, which is then sent to a generative AI model capable of interpreting the content and generating a 3D representation in `.glb` format. The model is then stored and a download link is returned to the user. ![image](https://i.postimg.cc/1Xd20z4R/3d.png) --- ### **Main Steps** 1. **Trigger Node**: Initiates the workflow either via HTTP request, webhook, or manual execution. 2. **Image Upload or Input**: The image is acquired via direct upload or URL input. 3. **API Integration**: The image is sent to a 3D generation API (e.g., a service like Kaedim, Luma Labs, or a custom AI model). 4. **Model Generation**: The external API processes the image and creates a 3D model. 5. **File Storage**: The resulting 3D model is stored in cloud storage (e.g., S3, Google Drive, or a local server). 6. **Response to User**: A download link for the 3D model is returned to the user via the same communication channel (HTTP response, email, or chat). --- ### **Advantages** * **Automation**: Eliminates the need for manual 3D modeling, saving time for artists, developers, and designers. * **AI-Powered**: Leverages AI to generate realistic and usable 3D models from simple 2D inputs. * **Scalability**: Can be triggered automatically and scaled up to handle many requests via n8n's automation. * **Integration-Friendly**: Easily extendable with other services like Discord, Telegram, or marketplaces for 3D assets. * **No-Code Configuration**: Built with n8n's visual interface, making it editable without programming knowledge. --- ### **How It Works** 1. **Trigger**: The workflow can be started manually (When clicking “Test workflow”) or automatically at scheduled intervals (Schedule Trigger). 2. **Data Retrieval**: The Get new image node fetches data from a Google Sheet, including the model image, product image, and product ID. 3. **3D Image Creation**: The Create 3D Image node sends the image data to the Fal.run API (Trellis) to generate a 3D model. 4. **Status Check**: The workflow periodically checks the request status (Get status and Wait 60 sec.) until the job is marked as COMPLETED. 5. **Result Processing**: Once completed, the 3D model URL is retrieved (Get Url 3D image), the file is downloaded (Get File 3D image), and uploaded to Google Drive (Upload 3D Image). 6. **Sheet Update**: The final 3D model URL is written back to the Google Sheet (Update result). --- ### **Set Up Steps** 1. **Prepare Google Sheet**: - Create a Google Sheet with columns: **IMAGE MODEL** and **3D RESULT** (empty). - Example sheet: [Google Sheet Template](https://docs.google.com/spreadsheets/d/1C0Et6X3Zwr_6CxeNjhLpDwjAfIGeUvLGFawckKb0utY/edit?usp=sharing). 2. **Obtain Fal.run API Key**: - Sign up at [Fal.ai](https://fal.ai/) and get an API key. - Configure the **Authorization** header in the Create 3D Image node with `Key YOURAPIKEY`. 3. **Configure Workflow Execution**: - Run manually via the **Test workflow** button. - For automation, set up the **Schedule Trigger** node (e.g., every 5 minutes). 4. **Verify Credentials**: Ensure Google Sheets, Google Drive, and Fal.run API credentials are correctly set in n8n. Once configured, the workflow processes new entries in the Google Sheet, generates 3D models, and updates the results automatically. --- ### **Need help customizing?** [Contact me](mailto:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).

    n8nFree

  5. Automate News Monitoring and Email Summaries with Perplexity.ai

    This workflow automates the monitoring of specific news events and sends concise email summaries using Perplexity.ai's language models. Ideal for users needing timely updates on topics of interest, it eliminates the need for manual news checks.

    n8nFree

  6. Automate Job Search and Matching with Adzuna API, GPT-3.5, and Google Sheets

    Job Search Automation Workflow Streamline Job Discovery with API-Powered Intelligence This workflow template transforms the job search process by leveraging the Adzuna API and AI to automatically find, summarize, and evaluate job opportunities. Unlike traditional RSS-based job search tools, this workflow connects directly to Adzuna's comprehensive job API for real-time, high-quality job data. Workflow Overview The Job Search Automation Workflow follows a streamlined process: - Define job titles to search for - Fetch current job listings from Adzuna's API - Split individual job results for processing - Use AI to extract and summarize key job information - Score each job against candidate profiles - Organize results for easy review This automation eliminates manual searching across job boards and provides objective evaluation of opportunities, saving valuable time for both job seekers and professionals who support them. Technical Implementation The workflow is built with a focus on efficiency and extensibility: - API Integration: Direct connection to Adzuna's job API ensures access to current listings with comprehensive details - AI Processing: Leverages OpenAI's GPT models to intelligently summarize job descriptions and evaluate candidate fit - Modular Design: Each node serves a specific purpose, making the workflow easy to understand and customize - Scalable Architecture: Can be expanded to include additional job sources or evaluation criteria Use Cases This template serves multiple user groups: - Job Seekers: Automate discovery of relevant positions matching your skills - Recruiters: Quickly identify quality positions for your candidate pool - Career Coaches: Systematically help clients find suitable positions - AI Automation Builders: Learn how to integrate job APIs with AI evaluation systems Prerequisites To use this workflow, you'll need: - An Adzuna API key (available at Adzuna.com) - An n8n instance (cloud or self-hosted) - OpenAI API credentials (or compatible alternative) Getting Started - Import this template to your n8n instance - Configure your Adzuna API credentials - Set up your OpenAI API connection - Customize job titles and candidate profiles - Execute the workflow to start discovering opportunities Customization Options The workflow can be easily adapted to your specific needs: - Modify job search parameters (location, industry, etc.) - Adjust AI prompts for different summarization styles - Customize scoring criteria based on specific skills or requirements - Add nodes to integrate with other tools in your workflow Why This Approach Matters Traditional job search methods often rely on RSS feeds, which can be limited in detail and frequency of updates. By connecting directly to the Adzuna API, this workflow ensures you're always working with the most current job data available. The AI-powered evaluation provides objective scoring of how well each position matches candidate profiles, helping prioritize applications for positions with the highest potential fit. Whether you're a job seeker looking to streamline your search, a professional helping others find opportunities, or an automation enthusiast interested in API integrations, this template provides a solid foundation for more efficient job discovery and evaluation.

    n8nFree

  7. Automate Personalized WhatsApp Quizzes with GPT-4 and Supabase

    This workflow creates a personalized quiz assistant on WhatsApp using GPT-4 and Supabase, capturing user data and delivering tailored quizzes.

    n8nFree

  8. Automate AI Music and Video Creation from Telegram Ideas

    This workflow automates the creation of AI-generated music tracks, cover art, and music videos from ideas submitted via Telegram, managing the process through Google Sheets.

    n8nFree

  9. Transform YouTube Playlists into Interactive Chatbot Knowledge Bases

    This n8n workflow converts YouTube playlists or individual videos into interactive knowledge bases, allowing users to chat with the content and receive summaries and insights without watching the videos.

    n8nFree

  10. Automated Phone Interview Evaluation with Vapi, GPT-4o & Sheets

    Processes phone interview transcripts via webhook, uses GPT-4o-mini for AI evaluation against criteria, extracts candidate data, and saves results to Google Sheets for HR teams.

    n8n$19.99

  11. Automate YouTube Video Summaries to Obsidian via Dropbox

    Automatically fetch YouTube videos from a playlist, generate detailed summaries using OpenAI, and save them as Markdown files in Dropbox for seamless integration with Obsidian.

    n8nFree

  12. Extract Product Info from Website Screenshots with Dumpling AI + Sheets

    ### What this workflow does This workflow extracts product details—like name, price, discount, and rating—from website screenshots using Dumpling AI. It starts when a new product page URL is added to a Google Sheet, captures a screenshot of that page, extracts visible product info from the image, and writes the results back into the sheet. ### What problem is this workflow solving? Many product pages block traditional scraping tools or use unstructured layouts. This workflow bypasses HTML limitations by using visual AI extraction, making it reliable even when content is embedded in images or hard to parse with code. ### Who is this for? This is ideal for eCommerce researchers, pricing analysts, marketers, or anyone building a product database from websites without needing to code or maintain complex scrapers. ### Setup 1. Create a Google Sheet with a column named **Site** (or update the trigger). 2. Add your product page URLs in this column—one per row. 3. Connect your Google Sheets and Dumpling AI credentials in n8n. 4. Ensure your Dumpling AI account has API access for screenshots and extraction. ### How to customize the workflow - **Prompt adjustment**: In the “Extract Text from Screenshot” node, you can modify the prompt to extract other information like brand name, delivery time, or availability. - **Add more fields**: After the extraction, edit the “Format Extracted Data” node to map additional fields from the response to your Google Sheet columns. - **Change output destination**: You can easily replace the Google Sheets module with Airtable, Notion, or another app if preferred. > This works best when the product data is clearly visible in the screenshot. > It won't extract info that's hidden behind popups or loaded via user interaction.

    n8nFree

  13. AI-Powered Speechwriting Coach via Telegram with OpenAI and Google Gemini

    This n8n workflow serves as an AI speechwriting coach, accessible through Telegram. It provides feedback on speech drafts, refines content iteratively, and generates improved speeches using AI models from OpenAI and Google Gemini.

    n8nFree

  14. Automate AI Image Generation and Upload with Google Sheets and Drive

    Streamline the creation of AI-generated images from prompts in Google Sheets, automatically upload them to Google Drive, and log the results back into the sheet.

    n8nFree

  15. Automate WordPress Blog Creation from Google Sheets with ChatGPT Enhancements

    Streamline your content creation process by automatically generating WordPress blog posts using data from Google Sheets, enhanced with ChatGPT completions.

    MakeFree

  16. Voice-Activated Workflow Automation with Vagent.io, Notion, and Google Calendar

    Enable seamless voice interaction with AI agents to automate tasks and manage calendars using Vagent.io, Notion, and Google Calendar.

    n8nFree

  17. Create a Humorous Telegram Bot with AI and Postgres

    Build a witty Telegram bot using n8n, OpenRouter, and Postgres to deliver jokes, motivational quotes, and playful roasts. This workflow tracks user interactions and provides statistics and leaderboards.

    n8nFree

  18. Automate Podcast Script Creation from Telegram Voice Notes

    Effortlessly convert Telegram voice messages into structured podcast scripts in Notion using AI transcription and analysis.

    n8nFree

  19. Stock Fundamental Analysis & AI-Powered Reports with Mistral and AlphaVantage

    # Fundamental Analysis, Stock Analysis, and AI Integration in the Fundamental Analysis Tool --- ## Overview of the Tool The **Fundamental Analysis Tool** is an automated workflow designed to evaluate a stock's fundamentals using financial data and AI-driven insights. Built on the n8n automation platform, it: 1. **Collects** financial data for a user-specified stock from AlphaVantage. 2. **Processes** and structures this data for analysis. 3. **Analyzes** the data using the Mistral AI model to provide expert-level insights. 4. **Generates** a visually appealing HTML report with charts and delivers it via email. The tool is triggered by a form where users input a **stock symbol** (e.g., NVDA for NVIDIA) and their **email address**. From there, it follows a three-stage process: **data retrieval**, **data processing**, and **AI analysis with report generation**. --- ## 1. Fundamental Analysis: The Foundation Fundamental analysis involves evaluating a company's intrinsic value by examining its financial health, competitive position, and market environment. This tool performs fundamental analysis by: ### Data Retrieval - **Data Types**: Six types of data are retrieved via HTTP requests: - **Overview**: General company details (e.g., sector, industry, market cap). - **Income Statement**: Revenue, net income, and profitability metrics. - **Balance Sheet**: Assets, liabilities, and equity. - **Cash Flow**: Operating, investing, and financing cash flows. - **Earnings Calendar**: Upcoming earnings events. - **Earnings**: Historical earnings data (annual and quarterly). ### Key Metrics Analyzed The tool structures this data into **8 categories** critical to fundamental analysis, as defined in the Code1 node: 1. **Economic Moats & Competitive Advantage**: Assesses sustainable advantages (e.g., R&D spending, gross profit). 2. **Financial Health & Profitability**: Examines ROE, debt levels, and dividend yield. 3. **Valuation & Market Sentiment**: Evaluates P/E ratio, PEG ratio, and book value. 4. **Management & Capital Allocation**: Reviews market cap justification and cash allocation (e.g., R&D, buybacks). 5. **Industry & Risk Exposure**: Analyzes revenue cyclicality and geopolitical risks. 6. **Key Metrics to Probe**: Investigates net income trends and gross margins. 7. **Red Flags**: Identifies risks like inventory issues or stock dilution. 8. **Final Checklist**: Summarizes pricing power and risk/reward potential. These categories cover the core pillars of fundamental analysis, ensuring a holistic evaluation of the stock's intrinsic value and risks. --- ## 2. Stock Analysis: Tailored Insights The tool performs stock-specific analysis by focusing on the user-provided **stock symbol**. Here's how it tailors the process: ### Input and Customization - **Form Submission**: Users enter a stock symbol (e.g., NVDA) and email via the On Form Submission node. - **Dynamic Data Fetching**: The Set Variables node passes the stock symbol to the API calls, ensuring the analysis is specific to the chosen stock. ### Processing for Relevance - **Data Filtering**: The workflow limits historical data to the **last 5 years** (via the Limit node), focusing on recent trends. - **Merging and Cleaning**: The Merge and Code2 nodes combine and refine the data, removing irrelevant fields (e.g., quarterly reports) and aggregating annual reports for consistency. ### Output - The final report is titled with the stock's name (e.g., Fundamental Analysis - NVIDIA), ensuring the analysis is clearly tied to the user's chosen stock. This stock-specific approach makes the tool practical for investors analyzing individual companies rather than broad market trends. --- ## 3. AI Integration: Expert-Level Insights The integration of **AI** (via the Mistral model or others) is what sets this tool apart, automating complex analysis and report generation. Here's how AI is woven into the workflow: ### Data Preparation for AI - **Structuring**: The Code1 node organizes the raw data into a JSON schema aligned with the eight fundamental analysis categories. - This structured data is fed into the AI for analysis. ### AI Analysis - **Node**: Basic LLM Chain uses the **Mistral AI model**. - **Prompt**: The AI is instructed to act as an expert financial advisor with 50 years of experience and answer specific questions for each category, such as: - *Economic Moats*: What sustainable competitive advantages protect the company's margins? - *Financial Health*: Is ROE driven by leverage or true profitability? - *Red Flags*: Are supply chain issues a concern? - **Output**: The AI generates a JSON response with detailed insights, e.g.: ```json { "Economic Moats & Competitive Advantage": "NVIDIA's leadership in GPU technology and strong R&D investment...", "Financial Health & Profitability": "ROE of 25% is exceptional, driven by profitability rather than leverage...", ... } ```

    n8nFree

  20. Generate Recipes from Ingredients with Ollama AI Chef Agent

    ## What It Does The Chef Agent is your AI-powered kitchen companion—ready to turn leftover ingredients into meal inspiration. It's a simple, fun n8n automation that: - Accepts a list of ingredients via webhook - Uses Ollama AI to suggest 5 creative recipes or food ideas - Recommends up to 3 missing ingredients to improve the dish - Returns a fallback message if the AI is unavailable - Includes setup notes for beginners ## Requirements - An active n8n instance (local or hosted) - Ollama AI running locally (or another LLM via HTTP request) - A webhook endpoint (defaults to `/lets-cook`) ## Why You'll Love It - Fully customizable for your use case or favorite LLM - Great intro to AI + workflow automation - Comes with playful Clown Mutiny flair: > "Powered by Clown Mutiny's taste-bud liberation division." ## Installation 1. Import the provided JSON template into your n8n workspace. 2. Configure your AI node to match your local Ollama instance. 3. Trigger the flow by sending a `POST` request to the webhook: ```json { "ingredients": "eggs, rice, spinach" } ```

    n8nFree

  21. Automate Image Data Extraction with Gemini AI via API

    This n8n workflow creates an API endpoint for extracting structured data from images using Gemini AI. It processes an image URL and returns extracted details in JSON format, ideal for automating document processing tasks.

    n8nFree

  22. Automate Analysis and Storage of Hugging Face Papers in Notion

    This workflow automates the retrieval of paper summaries from Hugging Face, analyzes them using OpenAI, and stores the results in Notion, ensuring efficient management of academic resources.

    n8nFree
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