AI Workflows
Artificial Intelligence tools and workflows
Automate Voice Cloning with Zyphra Zonos API via n8n
Effortlessly convert text to natural-sounding speech using AI voice cloning with Zyphra Zonos API. Ideal for developers and content creators seeking consistent voice output.
n8n$14.99Automate ISO 26262 Safety Analysis for Automotive Compliance
Streamline ISO 26262 compliance by automating safety analysis for automotive systems, ensuring rigorous audit standards and reducing manual effort.
n8n$14.99Automate Article Creation with AI Agents and Perplexity for Citations
This workflow automates the creation of well-researched articles using AI agents and Perplexity for accurate citations. It streamlines the research and writing process, ensuring high-quality content with credible sources.
n8n$14.99Legal Case Research Extractor and Data Miner with Bright Data MCP & Google Gemini
### Notice Community nodes can only be installed on self-hosted instances of n8n. ### Who this is for The Legal Case Research Extractor is a powerful automated workflow designed for legal tech teams, researchers, law firms, and data scientists focused on transforming unstructured legal case data into actionable, structured insights. This workflow is tailored for: - Legal Researchers automating case law data mining - Litigation Support Teams handling large volumes of case records - Legal Tech Startups building AI-powered legal research assistants - Compliance Analysts extracting case-specific insights - AI Developers working on legal NLP, summarization, and search engines ### What problem is this workflow solving? Legal case data is often locked in semi-structured or raw HTML formats, scattered across jurisdiction-specific websites. Manually extracting and processing this data is tedious and inefficient. This workflow automates: - Extraction of legal case data via Bright Data's powerful MCP infrastructure - Parsing of HTML into clean, readable text using Google Gemini LLM - Structuring and delivering the output through webhook and file storage ### What this workflow does **Input** - Set the Legal Case Research URL node is responsible for setting the legal case URL for the data extraction. **Bright Data MCP Data Extractor** - Bright Data MCP Client For Legal Case Research node is responsible for the legal case extraction via the Bright Data MCP tool - scrape_as_html **Case Extractor** - Google Gemini based Case Extractor is responsible for producing a paginated list of cases **Loop through Legal Case URLs** - Receives a collection of legal case links to process - Each URL represents a different case from a target legal website **Bright Data MCP Scraping** - Utilizes Bright Data's scrape_as_html MCP mode - Retrieves raw HTML content of each legal case **Google Gemini LLM Extraction** - Transforms raw HTML into clean, structured text - Performs additional information extraction if required (e.g., case summary, court, jurisdiction etc.) **Webhook Notification** - Sends extracted legal case content to a configurable webhook URL - Enables downstream processing or storage in legal databases **Binary Conversion & File Persistence** - Converts the structured text to binary format - Saves the final response to disk for archival or further processing ### Pre-conditions 1. Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - [model-context-protocol](https://www.anthropic.com/news/model-context-protocol) 2. You need to have the [Bright Data](https://brightdata.com/) account and do the necessary setup as mentioned in the **Setup** section below. 3. You need to have the Google Gemini API Key. Visit [Google AI Studio](https://aistudio.google.com/) 4. You need to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp) 5. You need to install the [n8n-nodes-mcp](https://github.com/nerding-io/n8n-nodes-mcp) ### Setup 1. Please make sure to set up n8n locally with MCP Servers by navigating to [n8n-nodes-mcp](https://www.youtube.com/watch?v=NUb73ErUCsA) 2. Please make sure to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp) on your local machine. 3. Sign up at [Bright Data](https://brightdata.com/). 4. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. 5. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. 6. In n8n, configure the Google Gemini (PaLM) API account with the Google Gemini API key (or access through Vertex AI or proxy). 7. In n8n, configure the credentials to connect with MCP Client (SDIO) account with the Bright Data MCP Server as shown below.  Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token> ### How to customize this workflow to your needs **Target New Legal Portals** - Modify the legal case input URLs to scrape from different state or federal case databases **Customize LLM Extraction** - Modify the prompt to extract specific fields: case number, plaintiff, case summary, outcome, legal precedents etc. - Add a summarization step if needed **Enhance Loop Handling** - Integrate with a Google Sheet or API to dynamically fetch case URLs - Add error handling logic to skip failed cases and log them **Improve Security & Compliance** - Redact sensitive information before sending via webhook - Store processed case data in encrypted cloud storage **Output Formats** - Save as PDF, JSON, or Markdown - Enable output to cloud storage (S3, Google Drive) or legal document management systems
n8n$14.99Automate AI Content Creation and Management with Google Drive and Sheets
Streamline your content creation process by automating article generation with AI, organizing files in Google Drive, and tracking progress in Google Sheets. Ideal for marketers, bloggers, and businesses.
n8n$24.99Reddit Sentiment Analysis for Apple WWDC25 with GeminAI and Google Sheets
This workflow automates sentiment analysis of Reddit posts related to Apple's WWDC25 event. It extracts data, categorizes posts, analyzes the sentiment of comments, and updates a Google Sheet with the results. ### Prerequisites 1. **Bright Data Account:** You need a Bright Data account to scrape Reddit data. Ensure you have the correct permissions to use their API. [https://brightdata.com/](https://brightdata.com/) 2. **Google Sheets API Credentials:** Enable the Google Sheets API in your Google Cloud project and create credentials (OAuth 2.0 Client IDs). 3. **Google Gemini API Credentials:** You need a Gemini API key to run the sentiment analysis. Ensure you have the correct permissions to use their API. [https://ai.google.dev/](https://ai.google.dev/). You can use any other models of choice. ### Setup 1. **Import the Workflow:** Import the provided JSON workflow into your n8n instance. 2. **Configure Bright Data Credentials:** In the scrape Reddit and the get status nodes, in Header Parameters find the Authorization field, replace `Bearer 1234` with your Bright Data API key. Apply this to every node that utilizes your Bright Data API Key. 3. **Set up the Google Sheets API credentials** - In the Append Sentiments node, set up the Google Sheets API by connecting your Google Sheets account through OAuth 2 credentials. 4. **Configure the Google Gemini Credential ID** - In the Sentiment Analysis per comment node, set up the Google Gemini API by connecting your Google AI account through the API credentials. 5. **Configure Additional Parameters:** - In the scrape Reddit node, modify the JSON body to adjust the search term, date, or sort method. - In the Wait node, alter the Amount to adjust the polling interval for scraping status, it is set to 15 seconds by default. - In the ext Classifier node, customize the categories and descriptions to suit the sentiment analysis needs. Review categories such as WWDC events to ensure relevancy. - In the Sentiment Analysis per comment node, modify the system prompt template to improve context. ### Customization Options 1. Bright Data API parameters to adjust scraping behavior. 2. Wait node duration to optimize polling. 3. ext Classifier categories and descriptions. 4. Sentiment Analysis system prompt. ### Use Case Examples - **Brand Monitoring:** Track public sentiment towards Apple during and after the WWDC25 event. - **Product Feedback Analysis:** Gather insights into user reactions to new product announcements. - **Competitive Analysis:** Compare sentiment towards Apple's announcements versus competitors. - **Event Impact Assessment:** Measure the overall impact of the WWDC25 event on various aspects of Apple's business. ### Target Audiences - Marketing professionals in the tech industry, - Brand managers, - Product managers, - Market research analysts, - Social media managers ### Troubleshooting 1. Workflow fails to start. Check that all necessary credentials (Bright Data and Google Sheets API) are correctly configured and that the Bright Data API key is valid. 2. Data scraping fails. Verify the Bright Data API key, ensure the dataset ID is correct, and inspect the Bright Data dashboard for any issues with the scraping job. 3. Sentiment analysis is inaccurate. Refine the categories and descriptions in the ext Classifier node. Check that you have the correct Google Gemini API key, as the original is a placeholder. 4. Google Sheets are not updating. Ensure the Google Sheets API credentials have the necessary permissions to write to the specified spreadsheet and sheet. Check API usage limits. 5. Workflow does not produce the correct output. Check the data connections, by clicking the connections, and looking at which data is being produced. Check all formulas for errors. Happy productivity!
n8n$14.99Automate Gong Transcript Processing and Salesforce Enrichment
Transform Gong call transcripts into structured, enriched data for enhanced sales insights by integrating Salesforce and PeopleDataLabs.
n8n$14.99Automate 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.
n8n$9.99Stock 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...", ... } ```
n8n$24.99Automate Gong.io Sales Call Analysis with AI and CRM Integration
Streamline the analysis of Gong.io sales calls using Azure AI to extract valuable insights and automatically sync them with Notion and Salesforce for enhanced sales, marketing, and product strategies.
n8n$14.99Automated AI-Driven CV Filtering Using Google Drive and Sheets
This workflow automates the process of filtering CVs using AI, integrating Google Drive and Google Sheets for seamless data handling. It leverages a Large Language Model for advanced content analysis, ensuring accurate and efficient candidate evaluation.
n8n$9.99Automate OpenAI Model Fine-Tuning with Google Drive Integration
This n8n workflow automates the fine-tuning of OpenAI models by integrating with Google Drive to manage training files. It simplifies the process of uploading data and initiating model training, enhancing efficiency and reducing manual effort.
n8n$9.99Automate Telegram AI Assistant with Google and OpenAI Integration
Create a smart AI assistant in Telegram using n8n, integrating with Google services and OpenAI for seamless task automation.
n8n$19.99Automate Research Idea Generation from PDFs Using InfraNodus
This workflow identifies content gaps in PDF documents and generates research questions using InfraNodus GraphRAG, helping researchers bridge knowledge gaps efficiently.
n8n$14.99Automate Company Name Cleaning for Cold Emails Using AI and Google Sheets
Enhance your cold email campaigns by automatically cleaning and standardizing company names in Google Sheets using AI. This workflow removes unnecessary suffixes and taglines to improve personalization and engagement.
n8n$9.99Automate Sales Meeting Prep with AI & APIFY Sent to WhatsApp
This n8n template builds a meeting assistant that compiles timely reminders of upcoming meetings filled with email history and recent LinkedIn activity of other people on the invite. This is then discreetly sent via WhatsApp ensuring the user is always prepared, informed, and ready to impress! ## How it works - A scheduled trigger fires hourly to check for upcoming personal meetings. - When found, the invite is analyzed by an AI agent to pull email and LinkedIn details of the other invitees. - 2 subworkflows are then triggered for each invitee to (1) search for the last email correspondence with them and (2) scrape their LinkedIn profile + recent activity for social updates. - Using both available sources, another AI agent is used to summarize this information and generate a short meeting prep message for the user. - The notification is finally sent to the user's WhatsApp, allowing them ample time to review. ## How to use - There are a lot of moving parts in this template so in its current form, it's best to use this for personal rather than team calendars. - The LinkedIn scraping method used in this workflow requires you to paste in your LinkedIn cookies from your browser which essentially lets n8n impersonate you. You can retrieve this from the dev console or ask someone technical for help! **Note**: It may be wise to switch to other LinkedIn scraping approaches which do not impersonate your own account for production. ## Requirements - OpenAI for LLM - Gmail for Email - Google Calendar for upcoming events - WhatsApp Business account for notifications ## Customizing this workflow - Try adding information sources that are relevant to you and your invitees, such as company search, other social media sites, etc. - Create an on-demand version which doesn't rely on the scheduled trigger. Sometimes you want to prepare for meetings hours or days in advance where this could help immensely.
n8n$24.99Automate TikTok Video Transcription and Translation with OpenAI and Google Docs
This workflow automates the extraction, translation, and storage of TikTok video transcripts using OpenAI GPT-4 and Google Docs. It's ideal for content creators and marketers who need efficient, AI-powered text processing.
n8n$9.99Fetch Keywords From Google Sheet and Classify Them Using AI
## Who is this template for This template is for marketers, SEO specialists, or content managers who need to analyze keywords to identify which ones contain references to a specific area or topic, in this case - IT software, services, tools, or apps. ## Use case Automating the process of scanning a large list of keywords to determine if they reference known IT products or services (like ServiceNow, Salesforce, etc.), and updating a Google Sheet with this classification. This helps in categorizing keywords for targeted SEO campaigns, content creation, or market analysis. ## How this workflow works 1. Fetches keyword data from a Google Sheet. 2. Processes keywords in batches to prevent rate limiting. 3. Uses an AI agent (OpenAI) to analyze each keyword and determine if it contains a reference to an IT service/software. 4. Updates the original Google Sheet with the results in a Service? column. 5. Continues processing until all keywords are analyzed. ## Set up steps 1. Connect your Google Sheets account credentials. 2. Set the Google Sheet document ID (currently using Copy of Sheet1 1). 3. Configure the OpenAI API credentials for the AI agent. 4. Adjust the batch size (currently 6) if needed based on your API rate limits. 5. Ensure the Google Sheet has the required columns: Number, Keyword, and Service?  The AI agent's prompt is highly customizable to match different identification needs. For example, instead of looking for IT software/services, you could modify the prompt to identify: - Industry-specific terms (healthcare, finance, education) - Geographic references (cities, countries, regions) - Product categories (electronics, clothing, food) - Competitor brand mentions Here's how you could modify the prompt for different use cases: ``` // For identifying educational content keywords Check the keyword I provided and define if this keyword relates to educational content, courses, or learning materials and return yes or no. // For identifying local service keywords Check the keyword I provided and determine if it contains location-specific terms (city names, neighborhoods, regions) that suggest local service intent and return yes or no. // For identifying competitor mentions Check the keyword I provided and determine if it mentions any of our competitors (CompetitorA, CompetitorB, CompetitorC) and return yes or no. ```
n8n$4.99OpenAI GPT-3: Company Enrichment from Website Content
Enrich your company lists with OpenAI GPT-3 You'll get valuable information such as: - Market (B2B or B2C) - Industry - Target Audience - Value Proposition This will help you to: - Add more personalization to your outreach - Make informed decisions about which accounts to target I've made the process easy with an n8n workflow. Here is what it does: - Retrieve website URLs from Google Sheets - Extract the content for each website - Analyze it with GPT-3 - Update Google Sheets with GPT-3 data
n8n$9.99Automate Video Description Generation with Google Gemini AI
Leverage Google Gemini 2.0 Flash AI to automatically generate detailed descriptions of video content from any public URL, enhancing accessibility, content moderation, and media cataloging.
n8n$9.99Enhance Airtable Records with ChatGPT Insights
Automatically update and enrich Airtable records using ChatGPT to provide contextual insights, ensuring your data remains accurate and informative.
ZapierFreeAutomate Daily Meeting Summaries with Google Gemini AI and Slack
This workflow automates the process of summarizing daily meetings using Google Gemini AI and sends the summaries to a specified Slack channel. It retrieves events from Google Calendar, processes them with the AI model, and delivers concise summaries at a scheduled time.
n8n$9.99Automate Image Generation with Lumi AI and Replicate API
This workflow automates image generation using the Lumi AI model via the Replicate API, streamlining the process by managing API authentication, parameter configuration, and result retrieval.
n8n$9.99Interactive AI Chatbot with Custom JavaScript Color Selector
This workflow creates an AI-powered conversational agent that returns a random color, excluding specified colors, using custom JavaScript code. Ideal for dynamic user interactions and personalized responses.
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