AI Data Analysis Templates

This workflow enables the automation of data classification using a K-Nearest Neighbors (KNN) algorithm on a lands dataset. It integrates HTTP Webhooks to trigger the process, facilitating seamless AI data analysis. Users can automate the classification task, allowing for efficient data processing and the ability to derive insights from large datasets without manual intervention.

This n8n workflow enables automated analysis of comments received through a webhook by utilizing OpenAI's ChatGPT technology. It identifies the sentiment, generates a concise title, summarizes content, and extracts relevant tags. By automatically returning results in JSON format, it streamlines content analysis, providing valuable insights quickly and efficiently. This workflow is ideal for businesses and developers looking to enhance data-driven decision-making and improve content management processes.

This workflow efficiently retrieves research paper summaries from Hugging Face and uses OpenAI to analyze their content, then stores the results in a Notion database. It prevents duplicate entries by checking for existing papers in Notion, ensuring streamlined data management. This automation saves time, enhances data organization, and leverages AI for insightful analysis, providing significant value to researchers and data analysts.

This n8n workflow serves as an anomaly detection tool for a crops dataset through HTTP execution. It automates the data analysis process, ensuring efficient identification of irregularities in crop data. By leveraging AI data analysis, it reduces manual effort, improves accuracy, and accelerates decision-making for agricultural stakeholders, enhancing productivity and insights.

This n8n workflow allows users to analyze a URL using the Cortex analyzer and retrieve detailed job information related to the analysis. By triggering manually, it initiates a specific Cortex analyzer to process the URL. The workflow then gathers and presents the job details, helping users efficiently understand the analysis results. This automation saves time and ensures accuracy, making it invaluable for teams needing precise data insights quickly.

This n8n workflow automates the summarization and analysis of YouTube playlists and videos using AI. By integrating powerful data analysis tools, it provides detailed insights and summaries, saving users time and enhancing productivity. It is particularly beneficial for content creators and analysts seeking to efficiently process and interpret video content.

The 'Wait Schedule Create Webhook' workflow in n8n automates the scheduling and triggering of webhooks at predefined intervals. It seamlessly integrates Google Sheets, Langchain, and Facebook Graph API to enhance data handling and communication. This workflow streamlines processes by automating routine tasks, improving efficiency, and reducing manual intervention, making it invaluable for businesses seeking to optimize their operations.

This n8n workflow automates the categorization of LinkedIn contacts and sends personalized emails via Gmail, leveraging Langchain Open AI for sophisticated data analysis. It enhances LinkedIn relationship management by efficiently sorting contacts into specific groups and facilitating targeted communication, saving time and improving engagement.

This n8n workflow automates the creation of Google Sheets entries based on incoming Gmail messages. By integrating Langchain's capabilities, it efficiently parses and extracts crucial data from emails, converting it into structured format in Google Sheets. This streamlines data management, eliminates manual entry, and enhances productivity by ensuring accurate and timely data recording.

The 'Wait Splitout Create Webhook' workflow in n8n automates the management of incoming webhooks by splitting the received data for detailed analysis and storing results in Google Sheets. By integrating with Langchain, it leverages advanced language model capabilities to provide enhanced data insights and refined responses. This workflow is particularly beneficial for businesses that require efficient data handling and insightful analysis, streamlining operations and improving decision-making processes.

This workflow automates the retrieval and analysis of SEO keyword search volume data using the Google Ads API. It captures metrics such as monthly search volume, historical trends, keyword difficulty scores, and competition metrics, thus enabling businesses to make informed decisions based on comprehensive data. By automating this process, users benefit from time savings, increased accuracy, and the ability to focus on strategic planning instead of manual data gathering.

The 'HTTP Aggregate Import Webhook' workflow empowers users to efficiently manage data reception and aggregation from multiple HTTP requests. Utilizing Langchain tools, it processes incoming webhooks swiftly, ensuring seamless data integration for applications. This automation enhances data handling efficiency and reduces manual workload, making it indispensable for dynamic data-driven environments.

The 'Gemini AI Video Analysis' workflow in n8n automates video content analysis using AI. It leverages HTTP webhook triggers to initiate video analysis tasks, providing insights into video content without manual intervention. This automation enhances efficiency by quickly processing large volumes of video data, making it invaluable for media companies and content creators who need to analyze video content at scale.

This workflow automates the extraction of actionable insights from meeting transcripts using AI, streamlining post-meeting processes. By integrating AI-driven analysis, it identifies key tasks, ensuring team members can effectively follow up on discussions. This enhances productivity by minimizing manual effort and improving task management accuracy.

The 'Wait Code Create Scheduled' workflow in n8n efficiently automates task scheduling based on real-time RSS feed updates. By leveraging Markdown for formatting and data splitting into manageable batches, it enhances task management. The workflow records outcomes in Google Sheets, providing streamlined tracking and increased efficiency for task management systems. Its automation capabilities reduce manual labor, ensure timely task scheduling, and enhance organizational productivity.

This workflow automates the extraction and analysis of data from forms, specifically designed for AI-driven CV screening. By leveraging n8n's powerful automation capabilities, this workflow ensures efficient data processing and analysis, transforming manual data extraction into a seamless, automated task. It reduces human error, accelerates the hiring process, and enhances data-driven decision-making for HR departments.

The 'Splitout Schedule Create Webhook' workflow in n8n automates task scheduling by dividing data into manageable batches. It integrates Microsoft Excel for efficient data handling and leverages Langchain's AI capabilities to enhance processing. This ensures tasks are executed without duplication, optimizing efficiency and accuracy. It's ideal for businesses needing streamlined data management and task planning.

🔄 How It Works? ✅ Step 1: Pull LinkedIn post details from an Excel file. ✅ Step 2: Scrape LinkedIn users who commented on the post. ✅ Step 3: Use AI sentiment analysis to find people who are genuinely interested. ✅ Step 4: Get detailed insights on the best leads instantly!   🎯 Final Data Output: ✔ Full Name ✔ Sentiment Score (Interested/Not Interested) ✔ Profile URL ✔ Location ✔ Key Skills ✔ Work Experience 💰 Why This is a Game-Changer? 💼 Recruiters → Find job seekers in seconds 📈 Marketers → Identify warm leads automatically 🛠️ Business Owners → Target potential clients with zero effort 🎯 Anyone who wants to scrape and analyze LinkedIn at scale

This workflow leverages LlamaParse and OpenAI within n8n to automate invoice data extraction. It efficiently processes invoices by parsing essential information, reducing manual data entry. Key benefits include increased accuracy, speed, and resource efficiency, making it valuable for businesses needing streamlined invoice processing.

This n8n workflow automates the enrichment of company lists by integrating Google Sheets and OpenAI. It extracts website content from company domains listed in a Google Sheet, uses OpenAI to analyze and determine key business attributes such as value proposition, industry, target audience, and market, and updates the sheet with enriched insights. This automation saves time, increases accuracy, and enhances decision-making by providing a deeper understanding of each company.

This n8n workflow efficiently automates the extraction of data from files received via a webhook. By transforming the raw data into a structured format, it facilitates seamless integration with Gmail for communication. This process not only streamlines data management but also enhances operational efficiency by reducing manual intervention, ensuring timely and accurate data handling.

This workflow leverages AI-powered research capabilities by integrating Jina AI Deep Search with a webhook in n8n, enabling the automated retrieval and analysis of complex data sets. It enhances data analysis processes by providing precise search results, reducing manual effort, and accelerating decision-making. The workflow is ideal for organizations looking to optimize their data analysis operations with AI technology.

The 'Splitout Code Automation Webhook' workflow efficiently automates the extraction and segmentation of HTML content using Langchain and OpenAI's language models. It transforms unstructured data into manageable segments, generates embeddings, and stores results in Google Sheets for streamlined access. This enhances data analysis and decision-making processes by providing structured information quickly and accurately.

This workflow automates the process of analyzing Instagram Business post metrics and creating a content calendar using AI. By extracting data from Instagram, it evaluates performance and suggests new content ideas. The generated content plan is then saved to Google Sheets, providing a structured approach to content management. The workflow saves time, enhances content strategy, and leverages AI for insightful analytics, making it an invaluable tool for social media managers and marketers.

This n8n workflow leverages the Cortex analyzer to perform detailed analysis of a given URL, extracting comprehensive job details. It begins with a manual trigger and processes the URL through Cortex, retrieving job data using the job ID. This automated approach reduces manual effort, improves accuracy, and streamlines data analysis tasks, making it highly valuable for teams needing efficient URL analysis.

This workflow automates the process of comparing local Ollama Vision models through Google Docs using n8n. By integrating with Google Docs, it streamlines the analysis of different models, saving time and reducing manual effort. Users can efficiently find the best local models, enhancing decision-making and improving productivity in model selection tasks.

This n8n workflow serves as a tool for executing a KNN classifier on a lands dataset via an HTTP webhook. It streamlines the process of initiating machine learning tasks by automating data analysis through a web-based trigger. This workflow enhances efficiency by reducing manual intervention, allowing users to focus on interpreting results rather than setting up complex processes manually. Ideal for data analysts and AI practitioners, the workflow significantly saves time and resources.

**Product Introduction:** You can create a form on n8n through which you can collect leads from interested user's. You can also verify each user's email address to validate whether it's a valid email to make sure it lands on their inbox(suitable for those who have newletter / want's to send bulk email) The leads with valid email will then get saved as a leads with the relevant field data to gmail, google sheets and discord(through webhook). You can add/remove any integration you feel like. **Setup Guide:** 1. **Create Your Form:** Begin by logging into your n8n account and navigating to the workflow editor. You can then customize your form fields to gather relevant information from your prospects, such as name, email address, and any additional data you require. 2. **Email Verification:** After collecting the lead data, add an Email Verification node to validate each user's email address. This crucial step ensures that only genuine and deliverable email addresses are included in your lead database, maximizing the effectiveness of your outreach efforts. We have used hunter.io service in this, you can change it to any other service you need. 3. **Save Leads:** Next, incorporate nodes to save your verified leads to various platforms for streamlined management. Utilize the Gmail node to store lead information directly in your Gmail account, ensuring easy access and organization. Additionally, leverage the Google Sheets node to archive lead data in a spreadsheet for comprehensive tracking and analysis. 4. **Integrate with Discord:** For real-time notifications and collaboration, integrate n8n with Discord using the Webhook node. Configure the webhook to send lead information to your designated Discord channel, enabling your team to stay informed and coordinate effectively. 5. **Customize Integrations:** Tailor your workflow by adding or removing integrations based on your specific requirements. Whether you prefer to connect with additional platforms or streamline your workflow further, n8n offers unparalleled flexibility to adapt to your business needs. Experience the simplicity and efficiency of n8n to revolutionize your lead generation strategy and propel your success to new heights.

This workflow enriches company lists by extracting website content, analyzing it with OpenAI GPT-3 to determine market, industry, target audience, and value proposition, and then updating a Google Sheet with this information. It automates the process of gathering key insights about companies from their websites.

This n8n workflow integrates with Google's Keyword Planner API to automate the collection of crucial SEO keyword metrics, such as monthly search volume and historical trends. By parsing and preparing this data for database storage, it streamlines the SEO research process, enabling marketers to make data-driven decisions efficiently, saving time and improving strategic outcomes.

This n8n workflow template is designed to automate the aggregation and analysis of keyword data from Ahrefs for enhanced productivity in digital marketing strategies. By utilizing webhooks, it streamlines the process of collecting and organizing keyword insights, saving marketers significant time and effort. The workflow's automation capabilities enable users to focus on strategic decision-making rather than manual data handling, providing a robust solution for optimizing keyword research processes. This tool is essential for digital marketers looking to improve efficiency, gain deeper insights, and enhance the effectiveness of their keyword strategies.

This n8n workflow leverages HTTP manual automation to analyze screenshots using AI. It captures incoming HTTP requests with screenshots, processes the images through AI for detailed analysis, and returns actionable insights. This automation saves time by eliminating manual analysis, increases accuracy with AI-driven insights, and streamlines data processing for improved efficiency in data analysis tasks.

This workflow automates the extraction and analysis of website content from URLs listed in a Google Sheet. Using OpenAI's GPT-3, it determines key business insights such as market, industry, target audience, and value proposition. The results are then updated back into the Google Sheet. This streamlined process saves time, enhances data accuracy, and provides valuable business intelligence, making it indispensable for market researchers and business analysts.

This n8n workflow automates the process of extracting brand-related content, performing a detailed summary, and conducting sentiment analysis using Bright Data. It enables businesses to efficiently monitor brand perception and make data-driven decisions. The workflow eliminates manual data collection and analysis, saving time and improving accuracy, which is crucial for maintaining a competitive edge in today's market.

This workflow automates the process of parsing a candidate's resume PDF, converting it to an image, and using a multimodal AI model (like Google Gemini) to assess the candidate's qualifications for a specific role. It determines if the candidate should proceed to the next stage of the hiring process.

This n8n workflow streamlines the process of conducting technical stock analysis by integrating Telegram, Airtable, and a GPT-powered AI agent. Users can submit stock queries via Telegram, which the workflow processes to retrieve relevant stock data and charts. The AI agent then performs a detailed analysis, and the results are sent back to the user. This automation enhances efficiency by providing fast, accurate stock insights, making it invaluable for traders and investors seeking timely information.

The 'Wait Splitout Automation Webhook' workflow streamlines data processing by capturing incoming webhook requests, splitting them into manageable segments, and using OpenAI to generate insights. It integrates Gmail for notifications and utilizes HTTP requests for seamless API interactions, enhancing data handling efficiency and automating responses, providing significant time savings and accuracy improvements.

The 'Wait Splitout Automation Webhook' workflow in n8n is a powerful tool designed for effectively managing and processing incoming HTTP request data. This workflow employs advanced memory management features from Langchain to handle complex data execution and storage. By automating data splitting, it ensures efficient operations, reduces manual intervention, and enhances data processing accuracy. This solution is particularly beneficial for businesses looking to streamline their data workflows and improve operational efficiency.

This n8n workflow automates the analysis of Reddit posts using AI to identify potential business opportunities. It seamlessly integrates Google Sheets to organize and store the analyzed data, enabling users to make data-driven decisions. The workflow enhances efficiency by eliminating manual data collection and analysis, allowing businesses to quickly spot trends and insights from Reddit discussions, thereby accelerating market research and strategic planning.

This n8n workflow template accurately estimates token usage and AI model costs across various tasks by analyzing execution data. It retrieves this data and calculates token counts and costs, either through predefined static pricing or real-time data from the Jina AI API. The results are then logged into Google Sheets, offering transparency and detailed cost tracking. This automation is invaluable for businesses seeking to optimize their AI usage and manage expenses effectively, ensuring efficient resource allocation and budget management.

This n8n workflow automates the extraction and processing of text data from Google Drive documents using Langchain services. It splits text into chunks, generates embeddings, and supports retrieval-augmented question-answering. This enhances efficiency in accessing and querying document content, providing a seamless experience for users managing large volumes of text data.

This workflow streamlines ETF comparison by automatically retrieving real-time data such as dividends, fees, and performance metrics from the web using ISIN codes found in an Excel sheet. Triggered by a webhook from an Excel macro, it updates the Excel file with new calculations, saving time and enhancing accuracy for financial analysts and investors.

This n8n workflow automates the extraction and analysis of survey data using Qdrant, Python, and Information Extractor. It streamlines the process of gathering insights from large datasets by leveraging AI technologies, providing businesses with actionable intelligence while reducing manual effort and improving data accuracy. Ideal for data analysts and decision-makers.

This workflow enriches company data from a Google Sheet by scraping website content, using OpenAI to extract key information like value proposition, industry, target audience, and market type (B2B/B2C), and then updates the Google Sheet with this enriched data. It leverages web scraping, AI-powered analysis, and data integration to streamline lead enrichment.

This workflow automates the transfer of n8n execution data to a Logstash instance, allowing for centralized logging and advanced data analysis. By retrieving, transforming, and pushing execution details, it streamlines the monitoring process and enhances data management. It also efficiently manages concurrent executions and tracks progress using static data storage, providing robust insights and improving operational efficiency for data teams.

The 'Wait Code Create Webhook' n8n workflow facilitates seamless data collection by generating a webhook URL and waiting for incoming HTTP requests. It integrates with Google Sheets to automatically log received data, eliminating manual data entry and enhancing data management efficiency. This workflow is essential for users needing real-time data collection and integration, ensuring streamlined processes and accurate data tracking.

This n8n workflow is designed to identify patterns of workplace discrimination by leveraging AI data analysis capabilities. It automates the collection and processing of data through webhooks, allowing organizations to spot trends and address issues proactively. By utilizing AI, this workflow enhances accuracy and efficiency in detecting discrimination patterns, providing a robust solution for HR departments and compliance teams. It significantly reduces manual effort while ensuring timely and insightful analysis, making it an invaluable tool for organizations focused on maintaining a fair workplace environment.

This n8n workflow automates the analysis of Reddit posts using AI to uncover business opportunities. By leveraging natural language processing, it identifies trends and insights from user discussions, providing businesses with data-driven strategies for growth. The workflow saves time, enhances decision-making, and provides a competitive edge in understanding market needs and customer sentiments.

This n8n workflow automates the extraction of spending history from Gmail transaction emails, classifies the transactions using AI, and systematically records the data into a Google Sheet for streamlined bookkeeping. By leveraging AI, it ensures accurate categorization, saving time and reducing manual errors, while providing a seamless integration between email data and financial records.

# Meta Ads Analyzer This n8n template builds an automated system to scrape, analyze, and extract insights from Meta advertising content. The workflow uses AI to perform deep analysis of video ads and organize the results in a structured format. **How it works** * The workflow connects to Facebook's Ad Library to scrape video ads based on a specified page ID. * Videos are filtered by reach and processed through Google's Gemini AI to analyze their content. * Each video is systematically analyzed for its hook, transcript, advertising format, concept, and narrative structure. * Results are processed through an AI agent that structures the data into standardized fields. * All analysis is saved to a Google Sheet for easy access and further processing. **How to use** Once you've set up your Credentials and configured the output: * Configure the Google Sheets connection for data output. * Specify the Meta Ad Library URL you want to analyze. * Adjust the maximum number of ads to scrape and analyze based on your needs. * Click "Test Workflow" to start the analysis process. **Requirements** * Apify account (for Meta Ad Library scraping) * Google Gemini * Google Sheets **Customizing this workflow** * Modify the AI prompts in the Settings node to extract different information from the videos. * Adjust the output formats in the AI Agent and Structured Output Parser nodes. * Change the Google Sheets mapping to match your desired output structure. * Increase the number of ads analyzed for more comprehensive research.

This n8n workflow automates the storage of Notion pages as vector documents in Supabase, utilizing OpenAI for enhanced data processing and analysis. By seamlessly integrating these platforms, the workflow streamlines data management, facilitates efficient information retrieval, and leverages AI capabilities to enhance data insights. Ideal for teams seeking to optimize their database operations and improve AI-driven data analysis.

This n8n workflow facilitates the seamless creation of AI-ready vector datasets by integrating Bright Data, Gemini, and Pinecone. It automates the process of collecting and transforming data into formats suitable for use in large language models (LLMs). By streamlining data preparation, this workflow enhances efficiency, reduces manual labor, and ensures high-quality data output, making it a valuable tool for AI developers and data scientists looking to optimize their dataset creation process.

This n8n workflow integrates AI capabilities with the Open-Meteo API to provide enhanced weather forecasting. By automating data retrieval and analysis, it delivers precise weather predictions, improving decision-making in weather-dependent industries. Users benefit from real-time insights, increased efficiency, and reduced manual data processing efforts.

The 'Splitout HTTP Send Webhook' n8n workflow streamlines data distribution by segmenting input data and sending it to multiple webhooks, utilizing Langchain tools for efficient data management and routing. This workflow enhances flexibility and efficiency in handling data across various automation tasks, providing significant benefits in terms of scalability and precision. It is invaluable for users who require robust data distribution capabilities, allowing for seamless integration with multiple endpoints.

This n8n workflow automates the anomaly detection process for crop datasets using HTTP execution and webhook integration. It allows for real-time data analysis and anomaly identification, providing timely insights for decision-making. By streamlining the detection of irregularities, it enhances the accuracy and efficiency of agricultural data management, offering substantial benefits in resource optimization and crop yield improvement.

This n8n workflow automates web queries and utilizes semantic re-ranking to enhance data retrieval processes. It intelligently processes incoming webhook requests, extracts datetime information, and applies advanced algorithms to prioritize search results based on relevance. Ideal for businesses seeking to streamline data analysis and improve decision-making accuracy, this workflow significantly reduces manual effort and increases efficiency. By automating these processes, users can save time, reduce errors, and focus on critical tasks.

This n8n workflow integrates Qdrant, Python, and an information extractor to provide community insights through advanced AI data analysis. It automates data collection, processing, and analysis, offering users valuable insights into community behavior and trends. By streamlining these processes, it saves time and reduces manual effort, making it an ideal tool for analysts and data-driven decision-makers.

This n8n workflow leverages HTTP execution and webhook capabilities to automate a KNN classifier for analyzing the lands dataset. By integrating AI data analysis with n8n's automation, users can streamline complex classification tasks, enhance data processing efficiency, and gain deeper insights without manual intervention. The workflow is designed to optimize time and accuracy in AI-driven data analysis projects, offering seamless integration and execution for data scientists and analysts.

The 'Splitout Code Create Webhook' n8n workflow efficiently automates data management by processing and parsing incoming webhook data using Langchain services. It splits this data into manageable batches, streamlining the handling process, and stores results in Google Sheets for easy access and further analysis. This workflow enhances data integration and processing speed, ensuring accurate and timely data handling, which is crucial for businesses relying on real-time data analytics.

This workflow automates the categorization of text inputs by utilizing a webhook to receive text data, which is then processed by the OpenAI Text Classifier to assign it to specific categories such as soccer, basketball, or drums. It enriches the data by mapping variables and adding the current date, offering an efficient solution for content classification. Ideal for businesses and developers looking to streamline data categorization processes, it enhances accuracy and saves time by reducing manual effort.

This workflow automates Pinterest data analysis by fetching pin performance metrics, identifying trending topics, and using AI to suggest content improvements. It integrates the Pinterest API, Airtable, OpenAI, and Gmail to deliver actionable insights to marketing managers, enhancing content strategy and boosting engagement. This process saves time and increases efficiency by eliminating manual data analysis.

This workflow effectively automates the sorting of datasets based on numerical values in ascending order, significantly enhancing data management processes. By streamlining the organization of data, users can reduce manual sorting efforts, improve accuracy, and maintain cleaner datasets. This results in increased operational efficiency and better resource allocation, as automation reduces the risk of human error and accelerates the decision-making process. It is especially beneficial for businesses handling large volumes of data that require organized structuring for analysis and reporting purposes, providing a reliable method to keep data consistent and accessible.

This n8n workflow automates the analysis of Strava data to provide personalized training insights for fitness enthusiasts. By connecting Strava with AI tools, it evaluates key performance metrics and sends tailored recommendations via email or WhatsApp, enhancing training efficiency and outcomes. The workflow streamlines data processing, reducing manual effort and enabling users to focus on their fitness goals.

This n8n workflow is designed to automate the setup of medoids for anomaly detection specifically in the context of a crops dataset. By efficiently handling the division of data into two types of medoids, it facilitates advanced AI-driven data analysis, ensuring precise anomaly identification and enhancing data quality monitoring. This automation saves significant time and reduces errors compared to manual data processing, making it invaluable for agricultural data analysts and researchers aiming to optimize crop production and quality control.

This workflow automates the extraction of key information from candidate resumes in PDF format by converting them to images and employing Google Gemini's multimodal AI to assess qualifications for specific roles. It mitigates issues with hidden prompts and uses conditional logic to decide if a candidate proceeds to the next recruitment stage, enhancing efficiency and accuracy in candidate screening.

This n8n workflow leverages a vector database for big data analysis, enabling AI agents to detect anomalies effectively. By integrating advanced data processing capabilities, it offers businesses the ability to analyze large datasets for AI-driven insights, improving decision-making and operational efficiency. The workflow is particularly beneficial for organizations seeking to enhance their AI models with precise data insights.

This n8n workflow automates the creation of a Noop trigger, integrating services like Langchain for language processing, Google Gemini for data management, and Gmail for communication. It streamlines data extraction and segmentation, enabling users to efficiently manage complex operations by automating repetitive tasks and enhancing data handling capabilities.

This workflow automates the collection and analysis of website analytics data from Umami, leveraging Openrouter AI to generate insightful summaries and improvement suggestions. The summarized data is then stored in a Baserow database. By comparing current and previous weekly traffic, it provides actionable insights for optimization, enhancing data-driven decision-making.

This n8n workflow automates the analysis of Gong.io sales calls by integrating with Notion for data management and Slack for real-time updates. It captures new calls, checks for duplicates in Notion, creates structured parent records, and utilizes AI for enhanced data processing. The workflow significantly enhances sales call analysis efficiency by automating data entry, duplicate checking, and providing timely alerts, thus improving decision-making and operational productivity.

This workflow streamlines the capture and analysis of marketing data by automating the extraction of UTM parameters from Shopify orders and storing them in a Baserow database. By utilizing the Shopify Admin API, it efficiently retrieves marketing insights, transforming them for easy storage and analysis in Baserow. This automation enhances campaign tracking, allowing businesses to optimize their marketing strategies based on accurate data insights, ultimately saving time and reducing manual data entry errors.

This n8n workflow leverages a specialized Ollama model, bespoke-minicheck, to detect hallucinations in AI-generated content. It provides an automated solution for ensuring the accuracy and reliability of AI outputs, which is crucial in data-sensitive applications. By integrating advanced AI analysis with n8n's automation capabilities, this workflow enhances data integrity and reduces manual verification efforts, making it a valuable tool for businesses relying on AI-driven insights.

This n8n workflow, known as the YouTube Video Analyzer with AI, automates the process of extracting insights from YouTube videos using advanced AI capabilities. By leveraging AI data analysis, it efficiently processes video content to provide detailed reports on viewer engagement, sentiment analysis, and trending topics. This workflow reduces manual analysis time, enhances accuracy, and provides valuable insights for content creators and marketers looking to optimize their video strategies.

This workflow leverages n8n to automate the analysis of cryptocurrency market data using CoinMarketCap and AI-powered tools. It retrieves real-time data, analyzes price trends, and generates comprehensive reports, enabling users to make informed investment decisions. This process saves time and enhances accuracy, providing valuable insights into market dynamics.

This n8n workflow efficiently automates the creation of AI-ready vector datasets for large language models by integrating Bright Data, Gemini, and Pinecone. It enhances the data collection, transformation, and storage processes, ensuring high accuracy and efficiency. This workflow is invaluable for streamlining dataset preparation, reducing manual effort, and improving data quality for AI applications.

This n8n workflow automates the extraction of structured data from various file formats and sends it via Gmail. Utilizing Langchain, it processes input files, identifies and extracts specific data points, and directly emails the extracted information to designated recipients. This automation saves time on manual data processing, enhances accuracy by reducing human errors, and ensures timely delivery of important information, making it invaluable for businesses that handle large volumes of data and require efficient communication channels.

The 'Limit Code Send Scheduled' workflow automates the sending of scheduled messages through Gmail and Discord, while managing file uploads in Google Drive. It efficiently divides data into manageable batches, ensuring seamless communication delivery and execution. This workflow enhances productivity by automating repetitive tasks, reducing errors, and ensuring timely message delivery through robust scheduling and data handling capabilities.

The 'Wait Redis Automate Triggered' workflow seamlessly integrates Redis with Langchain's information extraction and chat capabilities to automate data retrieval and processing. This workflow enables users to handle and respond to data-driven queries in real-time, enhancing productivity by automating tedious data management tasks, ensuring quick and accurate information processing, and improving overall workflow efficiency.

The 'Splitout Limit Create Webhook' n8n workflow efficiently processes incoming HTTP requests by splitting data into manageable segments, ensuring optimal data handling. It removes duplicates, maintains data integrity, and processes the data in batches. This automation is key for managing large data streams, reducing manual effort, and enhancing workflow efficiency.

The 'Joining different datasets' workflow in n8n automates the integration of multiple data sources into a single unified dataset, streamlining data analysis and enhancing reporting efficiency. By automating dataset merging, it ensures data consistency and availability, significantly improving decision-making processes. This workflow is especially beneficial for businesses seeking to optimize their data management and reporting capabilities.

This workflow automates the analysis of user feedback collected via Typeform by leveraging AWS Comprehend to determine sentiment. Negative feedback is automatically forwarded to a specified Mattermost channel, enabling teams to promptly address concerns. This process ensures efficient monitoring of customer sentiment, quick identification of issues, and enhanced response strategies.

This n8n workflow automates the enrichment of company data by extracting website content from URLs listed in a Google Sheet. It leverages OpenAI's GPT-3 to analyze and determine key business insights such as value proposition, industry, target market, and audience. The results are then updated back into the Google Sheet, streamlining data analysis and enhancing decision-making processes with AI-driven insights, saving time and ensuring accuracy in data handling.

This workflow leverages Qdrant, Python, and an Information Extractor to automate the analysis of customer data, providing businesses with deeper insights into customer behavior. By extracting information from diverse data sources, it enables companies to better understand their customers and personalize their strategies. The integration of AI data analysis tools streamlines the process, saving time and increasing accuracy in decision-making.

The 'Splitout Code Send Scheduled' workflow in n8n automates the process of splitting large datasets into smaller, more manageable batches for scheduled messaging on Slack. By integrating Langchain for advanced language processing, this workflow ensures seamless and efficient communication, reducing manual effort and improving operational efficiency. Beneficial for teams needing to streamline data handling and communication, this workflow enhances productivity by automating repetitive tasks and ensuring messages are sent timely and accurately.

**Step 1**: Start this manually or by webhook **Step 2**: - Fetch Reviews from Booking, Expedia, and Tripadvisor - Use Apify API to scrape reviews from multiple platforms. **Set up API requests for**: - Booking reviews using voyager~booking-reviews-scraper - Expedia reviews using tri_angle~expedia-hotels-com-reviews-scraper - Tripadvisor reviews using maxcopell~tripadvisor-reviews - Ensure you pass the correct hotel links from your database. **Step 3**: - Process Review Data - Extract relevant details such as: - Reviewer’s Name - Location - Rating - Review Title & Text - Liked and Disliked Aspects - Hotel Owner’s Response - Review Date Use the Set node in n8n to structure the data. **Step 4**: - Analyze Feedback Using AI - Integrate Google Gemini or ChatGPT to analyze review sentiments. - Identify common positive and negative themes. - Generate improvement suggestions based on guest feedback. **Step 5**: - Store Reviews in NOcoDB - Use NOcoDB as a structured database to store and manage review data. - - Map extracted review fields to your NOcoDB table. - Store review summaries and AI-generated suggestions for easy reference. Conclusion By automating hotel review collection and analysis using Apify, NOcoDB, and n8n, you can streamline feedback management and improve guest satisfaction efficiently. Implement these steps to make data-driven improvements for your hotel!

This n8n workflow template is designed to automate anomaly detection using medoids for a crops dataset. It effectively sets up two types of medoids, streamlining the process of identifying anomalies in agricultural data. This automation is crucial for AI-driven data analysis, providing enhanced accuracy and efficiency. By integrating this workflow, users can significantly reduce manual effort, improve data insights, and optimize decision-making processes in agriculture. The workflow is ideal for data analysts and agriculture professionals seeking to leverage AI for better crop management.

This workflow automatically collects cryptocurrency market data from CoinGecko every hour, formats the data into a concise market summary, and then publishes the update on X (formerly Twitter) and sends it via email using Gmail. It provides timely updates on crypto prices, ensuring users are informed without manual effort. By automating the entire process, this workflow saves time and increases efficiency, making it invaluable for crypto enthusiasts and traders who need up-to-date market information to make informed decisions.

The 'Splitout Limit Send Webhook' workflow efficiently manages large data sets by breaking them into smaller, manageable chunks and sending them via webhooks. By leveraging Langchain services, it ensures data is processed and formatted for seamless integration, enhancing workflow automation. This process reduces manual handling, minimizes errors, and improves data management efficiency.

The 'Splitout Redis Create Triggered' workflow in n8n automates data extraction from a Redis database and leverages Langchain's AI tools to analyze and process this data. It streamlines data handling by dynamically integrating AI-driven insights, enhancing memory management and generating contextually relevant responses. This workflow is valuable for teams needing efficient data processing and AI integration to support decision-making and improve operational efficiency.

This n8n workflow simplifies the task of discovering detailed company information by automating the search process using the uProc service. By entering a company name, it retrieves essential data, enhancing the accuracy and efficiency of data collection. This ensures users can quickly access relevant business insights, making it ideal for market research, lead generation, and competitive analysis.

This workflow automates the extraction of data from Thai bank slip images sent via LINE Bot using SpaceOCR, and systematically saves the extracted transaction details into a Google Sheet. It effectively processes both standard bank slips and PromptPay transactions, enhancing financial tracking by reducing manual data entry, improving accuracy, and streamlining the process. By automating these tasks, users can focus on more strategic financial analyses, thereby increasing productivity and reducing errors associated with manual processing.

The 'Splitout Code Create Webhook' n8n workflow automates the extraction of information from incoming HTTP requests and processes it using Langchain's AI capabilities. It then sends the output via Gmail, streamlining data extraction, transformation, and communication. This workflow is invaluable for businesses aiming to enhance efficiency by reducing manual data handling and ensuring accurate, timely information dissemination.

The 'Splitout Filter Create Scheduled' workflow in n8n automates managing large datasets from Google Sheets by splitting them into smaller, more manageable batches. It efficiently filters and processes each batch, sending results via Gmail and saving files to Google Drive. This enhances data handling efficiency, ensures timely communication, and reduces manual processing errors, providing significant time savings and improved accuracy for users. By automating these tasks, users can focus on more strategic activities.

This workflow automates company enrichment by retrieving website URLs from Google Sheets, extracting the content, and using OpenAI GPT-3 for analysis. The analysis determines the market, industry, target audience, and value proposition, updating Google Sheets with insights. This process saves time, enhances data accuracy, and provides valuable business intelligence insights efficiently.

This n8n template introduces the **Dynamic Prompts** Ai workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. **Check out the video demo I did for n8n Studio here**: [https://www.youtube.com/watch?v=_fNAD1u8BZw](https://www.youtube.com/watch?v=_fNAD1u8BZw) **Check out the example Airtable here:** [https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL](https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL) **Looking for the Baserow Version?** [https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/](https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/)

The 'Bitly Datetime Update Webhook' workflow automates the management of Bitly links by integrating Langchain services for sentiment analysis, summarization, and information extraction. This automation enhances link analytics, ensuring up-to-date insights and streamlined link management. Users can efficiently monitor and update link data, improving their digital marketing strategies and decision-making processes.

This workflow leverages the power of AI to enhance security analysis in GitHub by automatically checking pull requests for potential vulnerabilities. It uses OpenAI to process Git diff data and existing comments, generating context-aware insights. High-risk issues trigger a Slack notification. This improves security protocols by providing timely AI-driven insights and facilitates efficient collaboration among development teams.

This workflow automates the extraction of text from PDF files and images using Vertex AI, transforming the data into CSV format, and uploading it to Google Drive. By leveraging AI for text recognition and categorization, it significantly reduces manual data entry, streamlining the process of tracking financial transactions and managing expenses effectively.

This workflow automates the extraction and analysis of insights from YouTube video comments using AI. It transcribes video content, evaluates thumbnails, and gathers audience preferences to identify trends and optimize content for better engagement. By integrating YouTube, GoogleCloud, OpenAI, Apify, and Postgres, it streamlines data gathering and analysis, offering creators a powerful tool to enhance their content strategy.

This n8n workflow automates the detection of workplace discrimination patterns using AI-driven data analysis. By leveraging advanced algorithms, it analyzes communication data to identify potential discriminatory behavior, providing actionable insights for HR teams. This automation enhances organizational compliance and promotes a fair workplace environment by proactively addressing issues.

This n8n workflow automates the extraction and processing of data from files using Langchain's AI, and organizes the interpreted results into Google Sheets. It manages file inputs efficiently, enhances data understanding through AI, and ensures outputs are structured for easy analysis. Users benefit from streamlined data handling, improved interpretation, and organized storage, reducing manual effort and increasing accuracy.

This n8n workflow acts as an intelligent query orchestrator for AppSheet data, leveraging AI to enhance data interaction. It retrieves schema and taxonomy, then uses natural language processing to create and refine custom queries iteratively. This results in highly accurate data retrieval tailored to user needs, saving time and reducing manual effort.

The 'Filter HTTP Update Webhook' workflow is designed to streamline the process of handling HTTP requests by filtering and updating data in Google Sheets. It uses advanced Langchain tools to process data efficiently, ensuring that only pertinent information is captured and stored. This automation enhances data accuracy, reduces manual input, and saves time, making it valuable for businesses managing large data sets.

The 2016 Splitout Noop Automation Webhook workflow automates the sentiment analysis of YouTube comments using AI within n8n. It processes incoming comments, evaluates their sentiment, and categorizes them as positive, neutral, or negative. This streamlined approach ensures efficient data analysis, enabling users to gain insights into public opinion swiftly. By leveraging AI, users save time and enhance the accuracy of sentiment assessments, making it a valuable tool for content creators and marketers seeking to understand audience feedback.

The 'Aggregate Gmail Send Triggered' workflow automates the collection of emails from Gmail, processes their content using Langchain's AI tools, and generates structured outputs for efficient data analysis. This enhances communication by enabling users to quickly extract and interpret important information from their emails, reducing manual effort and improving overall productivity.

This workflow automates the analysis of comments from Hacker News for a specific story by clustering similar comments using a K-means algorithm, generating insights with AI, and storing results in Google Sheets. It helps in quickly identifying community consensus, frequently mentioned positives, and negatives, providing a comprehensive understanding of community sentiments and opinions.

The 'Wait Code Send Webhook' n8n workflow automates the process of triggering a webhook request upon receiving a designated code through an HTTP request. This workflow is particularly useful for tasks requiring real-time data transfer and communication, as it leverages HTTP requests and integrates email notifications to keep stakeholders informed. By automating these processes, it reduces manual intervention, increases efficiency, and ensures timely data flow, making it essential for businesses that rely on accurate and prompt data handling.

This workflow analyzes YouTube videos by extracting their transcripts, summarizing the content using AI, and sending the analysis via email. It extracts the video ID from a URL, generates a transcript, validates its existence, extracts the full text, analyzes it using AI, and sends an email with the analysis.

This n8n workflow automates the updating of Google Sheets based on real-time triggers from Airtop, effectively eliminating the need for manual data entry. By integrating these services, it ensures that data remains accurate and up-to-date, significantly reducing errors and saving time. It is particularly beneficial for users who rely on timely data updates for decision-making and operational efficiency.

This workflow transcribes sales calls using AssemblyAI, analyzes the transcript with OpenAI to extract key metrics, and stores the results in a Supabase database for further analysis and use in interfaces. It automates the process of gaining actionable insights from sales calls, improving sales performance and communication.

This n8n workflow automates the creation of sticky notes in a Postgres database triggered by events from the Langchain tool. It facilitates seamless note-taking and ensures critical information is efficiently captured and stored. Users benefit from improved productivity as it minimizes manual data entry and reduces the risk of missing important details, streamlining data management processes.

The CV Screening with OpenAI workflow automates the process of analyzing and evaluating resumes using AI. It leverages OpenAI's capabilities to quickly and accurately assess candidate qualifications, saving recruiters time and ensuring consistent evaluation criteria. This workflow is invaluable for HR departments looking to streamline recruitment and improve candidate selection processes.

This workflow automates the extraction and storage of text from chat images by utilizing AWS S3 for secure cloud storage. By converting visual data into text through image recognition, it enables seamless integration of information from chat images into digital workflows, enhancing accessibility and data management efficiency. It is particularly beneficial for organizations aiming to streamline data processing and ensure accurate text retrieval from images.

This n8n workflow template automates the process of decomposing large text documents into smaller, manageable segments for enhanced processing and embedding. By leveraging Langchain tools, it ensures efficient data loading and splitting, subsequently embedding the segments into the Qdrant vector database. This workflow significantly improves searchability and management of large text datasets, offering a robust solution for data-intensive applications and research projects. Its value lies in optimizing data handling workflows, saving time and reducing manual effort.

 This workflow is designed to capture and store Telegram messages in a ClickHouse database, providing an efficient solution for chat data analysis. Follow these steps to set it up:  1. **Configuration of the 'Record Messages' Node**: - Ensure your Telegram bot is set up as an administrator in the groups you wish to monitor. This is crucial for the bot to access messages. - Turn off the bot's privacy permissions. This enables it to read all group messages, necessary for proper recording. 2. **Settings in the 'Configuration' Node**: - Here, you need to set up the connection to your ClickHouse instance. - Edit the details in `CH_URL` with the URL of your ClickHouse server. Ensure the URL is correct and accessible from where n8n is running. 3. **Setup of the 'Save Data' Node**: - In this node, you will establish the credentials for accessing ClickHouse. - Enter the user (`CH_User`) and password (`CH_Password`) for your ClickHouse instance. These details are essential for n8n to store the collected data in the database. By following these steps, you can establish an effective workflow for collecting and storing Telegram messages in ClickHouse, facilitating the analysis and management of chat data. **Tutorial:** [https://nocodeopensource.io/optimizando-la-automatizacion-de-telegram-con-n8n-y-clickhouse/](https://nocodeopensource.io/optimizando-la-automatizacion-de-telegram-con-n8n-y-clickhouse/) ---

The AI Automated HR Workflow for CV Analysis and Candidate Evaluation utilizes n8n to automate the recruitment process by integrating Formtrigger, Extractfromfile, Merge, GoogleSheets, Googledrive, and Stickynote. This efficient workflow analyzes resumes, organizes data in Google Sheets, and stores files in Google Drive, streamlining candidate evaluation. By reducing manual effort and human error, it accelerates hiring timelines and improves accuracy, making it an invaluable tool for HR teams.

The 'Wait Code Create Webhook' workflow in n8n automates the creation and management of webhooks to handle incoming HTTP requests efficiently. It utilizes the Http Request and Split In Batches nodes to streamline data processing and initiate actions based on incoming information. This workflow is particularly beneficial for users needing to automate real-time data handling and subsequent task triggers, enhancing productivity and accuracy.

This workflow automates real-time data analysis by integrating multiple services. It uses a Webhook to receive data, processes it with a Function node for transformation, and finalizes it with a Set node for response customization. This setup enhances efficiency and accuracy, providing an automated solution for data-driven decision making, significantly reducing manual effort and improving response times.

This workflow automates the extraction of title tags and meta descriptions from URLs stored in Airtable, updating the records with this critical SEO data. By integrating Airtable and HTTP requests through n8n, it streamlines SEO analysis, saving time and reducing manual effort. This helps users maintain up-to-date metadata for SEO optimization, ensuring their web content is effectively indexed by search engines.

The AI Stock Investment Analyzer workflow leverages Gemini for cryptocurrency data and YFinance for stock insights, offering users a robust analysis of investment opportunities. This process automates data collection and analysis, enabling informed decisions by synthesizing real-time financial information, thus saving time and enhancing decision accuracy for investors.

This workflow automates the extraction and classification of data from files using Langchain, then integrates with Microsoft Outlook to send notifications. It enhances efficiency by automating data processing and communication, providing real-time updates and reducing manual intervention, thereby improving productivity and accuracy in data management.

The Reddit Comment Analyzer is an advanced n8n workflow designed to empower businesses by automating the monitoring of Reddit for brand mentions. It leverages sentiment analysis to assess user comments and collates these insights into Notion for further analysis. By using a combination of services like Reddit, Notion, and advanced data processing nodes, businesses can gain actionable insights into public perception and sentiment regarding their brand, enabling more informed decision-making and strategic planning. This workflow reduces manual monitoring efforts, enhances data accuracy, and provides a centralized repository for easy access to insights.

This n8n workflow automates the process of analyzing sentiment from feedback using Google Cloud Natural Language API and sends the results as a message on Mattermost. By integrating sentiment analysis with messaging, it helps organizations quickly gauge customer sentiment and facilitate timely communication, improving team responsiveness and decision-making. The workflow's automation saves time and ensures accurate sentiment interpretation, making it a valuable tool for customer support and marketing teams.

The 'Splitout Code Create Webhook' n8n workflow automates the handling of incoming HTTP requests, enabling seamless data management and processing. It splits incoming data and triggers downstream workflows, integrating with Gmail and Google Sheets to ensure efficient data recording and processing. This workflow enhances accuracy and saves time by automating repetitive tasks, providing a streamlined process for managing and analyzing data from multiple sources.

This n8n workflow template allows users to compare language models (LLMs) by integrating OpenAI with Google Sheets, automating the data analysis process. It provides a streamlined method for evaluating and summarizing data from LLMs, enhancing decision-making efficiency. By automating these tasks, users save time and increase accuracy in their analysis efforts.

This n8n workflow automates the process of analyzing any website by leveraging OpenAI to conduct a detailed on-page SEO audit. Users benefit from automated insights that highlight areas for improvement, optimize website performance, and enhance search engine visibility. This streamlined solution saves time, reduces manual effort, and boosts accuracy in identifying SEO improvements.

This n8n workflow processes image URLs to classify objects based on a pre-existing dataset of land types stored in a Qdrant vector database. By utilizing the K-nearest neighbors (KNN) algorithm, it finds similar images and determines the object's class through majority voting. It streamlines big data analysis for AI agents, enabling efficient image classification and decision-making processes.

This n8n workflow transforms user-provided text into SQL queries and visual data representations, eliminating the need for manual coding. By automating data manipulation, it allows for quick analysis and insights, enhancing decision-making efficiency. Users benefit from streamlined processes that save time and reduce errors, making data analysis more accessible and efficient.

This workflow extracts data from a PDF document using either Claude 3.5 Sonnet or Gemini 2.0 Flash, allowing users to compare the results, latency, and cost of each service. It downloads a PDF from Google Drive, converts it to base64, and then sends it to the selected AI model for information extraction based on a user-defined prompt.

The 'GitHub Aggregate Create Webhook' workflow streamlines the creation of GitHub repository webhooks by integrating Langchain and HTTP requests. This automation enables users to efficiently aggregate data from various sources and initiate actions based on repository events. It reduces manual effort, enhances data handling capabilities, and optimizes repository management by ensuring timely responses to critical events.

This n8n workflow automates the transfer of session data from Google Analytics to an Airtable database, allowing users to efficiently track website performance by country. It eliminates the need for manual data entry, reducing errors and saving time. By automating data retrieval and storage, it supports more accurate analysis and reporting, enhancing decision-making capabilities.

This n8n workflow automates the process of enriching company data in Google Sheets using OpenAI's GPT-3. It extracts website content to analyze and determine the company's value proposition, industry, target audience, and market, updating the sheet with this enriched data. This automation saves time, improves data accuracy, and enables better decision-making by providing comprehensive insights without manual effort.

This workflow automates the process of extracting and storing information from purchase receipts by analyzing receipt images. It uses intelligent image recognition to identify and digitize key purchase details, such as item names, prices, and totals. This streamlines record-keeping and expense tracking, reducing errors and saving time. By automating data entry, it enhances productivity and ensures accurate financial documentation, which is especially useful for businesses and individuals managing multiple transactions.

This n8n workflow automates the division of data into manageable batches, creates scheduled tasks, and enables seamless interaction between Google Sheets, Langchain Open AI, and Slack. It streamlines the organization and management of information, ensuring efficient communication and integration between these services. By automating repetitive tasks, this workflow saves time and reduces errors, enhancing productivity and enabling users to focus on more strategic activities.

This workflow automates image indexing for object-based search by integrating AI for object detection, cropping identified objects, and storing image URLs and metadata in Elasticsearch. It leverages Cloudflare for CDN capabilities and Cloudinary for optimized image management. This provides a streamlined, efficient solution for managing large image datasets, enhancing search accuracy, and optimizing resource usage.

This workflow streamlines the process of managing conference attendee registrations by integrating Typeform, Google Sheets, Mattermost, Google Calendar, and Gmail. It collects attendee data, updates spreadsheets, creates Mattermost accounts, assigns users to channels, updates calendar events, and sends personalized welcome emails. This automation reduces manual data entry, enhances communication, and ensures timely onboarding, providing efficiency and accuracy in managing event logistics.

This workflow leverages the power of AI to transform large spreadsheet data into a dynamic, interactive knowledge base. By integrating services like NocoDB, OpenAI, and Quickchart, users can perform natural language queries, conduct comparative analysis, and generate visualizations effortlessly. This enhances data interpretation, making insights more accessible and actionable.

This n8n workflow seamlessly integrates SerpBear, Openrouter, and Baserow to automate SEO analysis. It retrieves keyword ranking data from SerpBear, processes it using AI via Openrouter for a detailed analysis, and then stores the insights in a Baserow database. This automation not only enhances efficiency by eliminating manual data handling but also provides valuable, AI-driven insights into keyword performance, making it essential for data-driven SEO strategies.

The 'HubSpot Splitout Create Webhook' workflow automates the creation of webhooks in HubSpot using Langchain tools and Google Calendar. It efficiently manages events and data, enhancing operational efficiency by streamlining processes and reducing manual effort. This workflow is ideal for businesses looking to integrate HubSpot with calendar events seamlessly, ensuring timely and accurate data handling.

This n8n workflow serves as an anomaly detection tool for analyzing a crops dataset through HTTP execution. It automates the process of integrating various data sources and executing complex data analysis to identify irregular patterns in crop data. By leveraging this workflow, users can improve their data accuracy and operational efficiency, enabling timely interventions and resource allocation in agricultural practices. The workflow's automation capabilities significantly reduce manual effort, allowing for scalable and reliable analysis, essential for modern data-driven agriculture.

The 'Wait Code Send Webhook' workflow automates the synchronization of applications by waiting for a specific code that triggers a webhook. By integrating Microsoft Outlook for seamless communication, Langchain for advanced text classification and chat, and Excel for efficient data management, this workflow enhances operational efficiency and streamlines processes, saving time and reducing manual efforts.

This workflow automates the collection and sentiment analysis of customer feedback using OpenAI, then records the results in Google Sheets. It enhances efficiency by streamlining feedback processing, enabling businesses to quickly gain insights into customer sentiments, improve responsiveness, and make data-driven decisions to enhance customer satisfaction.

The 'Wait Filter Create Webhook' workflow in n8n is designed to automate the monitoring and execution of webhooks based on specific conditions. By integrating services like HTTP Request, Langchain Chain Llm, Langchain Lm Chat Open Ai, Gmail, and Google Sheets, it ensures that actions are only triggered when predefined criteria are met, enhancing efficiency and response times. This automation is particularly beneficial for businesses dealing with high volumes of data and requiring precise control over when and how webhooks are activated. The workflow streamlines operations, reduces manual oversight, and ensures that responses are timely and relevant. Its ability to handle complex conditions and multiple services makes it a valuable tool for enhancing data-driven decision-making processes.

This n8n workflow automates the creation of webhooks to trigger actions across multiple platforms such as Langchain Open AI, No Op, Google Drive, Gmail, and Read PDF. By connecting these services, users can streamline data operations, improve communication workflows, and enhance productivity. The integration enables efficient data processing, making it ideal for businesses looking to automate routine tasks and improve operational efficiency.

This workflow automates the process of extracting content from new Notion pages, converting it into vector embeddings using Google Gemini, and storing it in Pinecone for efficient semantic search and AI-driven insights. It monitors a Notion database for newly added pages, processes the text content, and updates a Pinecone vector store with the embeddings and relevant metadata.

This n8n workflow integrates AI capabilities with the Open-Meteo API to enhance weather forecasting by leveraging advanced algorithms for more accurate predictions. It automates data analysis, providing users with timely insights and improving decision-making processes. This solution is ideal for organizations seeking to optimize their operations through precise weather data.

This workflow leverages a self-hosted Large Language Model (LLM) to extract personal data from user input, transforming unstructured text into structured JSON. By integrating error handling, it ensures high accuracy and consistency, making it ideal for applications in data processing and analysis. The workflow is valuable for automating data extraction tasks, reducing manual effort, and enhancing data reliability.

This workflow automates the extraction of information from files using AI for CV screening processes. It leverages n8n's powerful automation capabilities to streamline data analysis, reducing manual intervention and improving accuracy. The workflow is especially beneficial for HR departments and recruiting agencies seeking to optimize their candidate evaluation processes, ultimately saving time and resources while enhancing data-driven decision-making.

The 'Splitout Code Create Webhook' workflow automates webhook creation using Langchain, enhancing communication across applications. By integrating ChatGPT, Google Sheets, and Gmail, it efficiently manages data flow, improves project management, and streamlines reporting. This automation reduces manual errors, saves time, and boosts productivity, making it invaluable for teams needing seamless data integration and processing.

This n8n workflow automates stock market technical analysis by integrating TradingView and GPT-4o to interpret charts and identify trading patterns. It delivers actionable insights via Telegram, enabling traders to make informed decisions without manual chart analysis. The workflow enhances decision-making efficiency and accuracy, providing real-time data-driven insights.

This n8n workflow automates the analysis of GitHub pull requests for vulnerabilities using OpenAI, and notifies relevant team members via Slack. By integrating these platforms, it enables faster detection and reporting of potential security issues, improving the efficiency and reliability of code review processes. Users benefit from streamlined collaboration, reduced manual effort, and enhanced security oversight.

Transform raw data into actionable business insights with DataSage AI, a powerful data analysis workflow powered by GPT-4. This intelligent AI agent performs comprehensive data exploration, statistical analysis, and generates visualization recommendations - all through a simple API endpoint. What This Workflow Does DataSage AI provides enterprise-grade data analysis capabilities with zero coding required. Simply send your dataset to the webhook endpoint, and receive back a structured analysis including: Complete data overview and quality assessment Key insights and pattern identification Detailed statistical analysis of numerical and categorical data Business recommendations based on the analysis Suggested data visualizations for better understanding Perfect For Data analysts needing to process multiple datasets quickly Business intelligence teams seeking automated insights Decision-makers who need data-driven recommendations Non-technical teams who need to extract value from data Startups without dedicated data science resources Technical Details Creates a dedicated webhook endpoint for data processing Automatically cleans and prepares data for analysis Leverages GPT-4 with a specialized data analyst system prompt Returns structured JSON with segmented analysis sections Handles both numerical and categorical data types Make It Your Own Customize the AI system prompt for your specific industry Add additional data processing steps for specialized datasets Connect to databases, spreadsheets, or BI tools to automate your entire data pipeline Add notification nodes to alert teams when important insights are discovered Give your organization the power of AI-driven data analysis without the complexity of building custom data science infrastructure.

This workflow automates the process of extracting data from invoice PDFs using Llama Cloud and Claude 3.5, then stores the extracted data in a Google Sheet. It retrieves an invoice from Google Drive, sends it to Llama Cloud for parsing, and uses an AI agent to extract key details before updating a Google Sheet.

This n8n workflow automates the enrichment of company data by extracting content from their websites and using OpenAI to analyze key aspects like value proposition, industry, target audience, and market. The analyzed data is then updated in a Google Sheet. This workflow streamlines data collection and analysis, saving time and improving accuracy in identifying business insights and market positioning.

This n8n workflow automates the updating of schedules in Google Sheets by integrating data from Langchain models through HTTP requests. It processes data in batches for efficiency, reducing manual input and ensuring timely updates. Key benefits include enhanced productivity, reduced errors, and seamless integration with existing tools, making it valuable for teams managing dynamic schedules.

This n8n workflow automates the extraction and analysis of images from PDFs, leveraging GPT-4o for advanced processing and Google Drive for storage and sharing. By automating these tasks, it significantly reduces manual effort and enhances the accuracy of data extraction and analysis, offering a seamless integration of AI capabilities with cloud storage solutions.

This n8n workflow template automates the process of storing Notion pages as vector documents into Supabase using OpenAI. By leveraging AI capabilities, it enables efficient data analysis and management. This integration helps users seamlessly transform and store data, enhancing accessibility and usability while reducing manual effort and potential errors.

This n8n workflow automates the extraction and summarization of Google Trend data using Bright Data and Google Gemini. By implementing an efficient HTTP webhook mechanism, it provides real-time insights and trends analysis. This automation significantly reduces manual data processing time, enhances data accuracy, and enables businesses to make informed decisions swiftly. Integration of AI tools ensures comprehensive data analysis, allowing users to focus on strategic tasks rather than operational ones.

The Youtube Outlier Detector workflow automates the detection of trending content by analyzing competitors' videos. It uses AI data analysis to identify patterns and outliers that signify rising trends in your niche. This workflow saves time, enhances strategic planning, and increases competitive advantage by providing actionable insights into competitor activities and emerging trends.

This n8n workflow automates the end-to-end process of document analysis and chatbot integration. By leveraging the Llama Cloud API for document parsing, Google Gemini for translation and analysis, and Pinecone for data storage, it extracts key information from uploaded documents. The analyzed data is then utilized by a chatbot to provide real-time user interaction and also sent via email. This automation enhances efficiency, reduces manual workload, and ensures accurate information dissemination.

This workflow automates the process of analyzing user feedback and sending alerts on Mattermost based on the sentiment of the feedback. It triggers when a user submits a Typeform response, analyzes the sentiment using Google Cloud Natural Language, and posts a message on a Mattermost channel if the sentiment is negative.

This n8n automation is designed to analyze cryptocurrency trends by extracting, processing, and interpreting candlestick charts using AI-powered agents. The workflow enhances technical analysis by integrating real-time market data, ensuring traders receive accurate and actionable insights. [](https://www.youtube.com/watch?v=XW03ztGgbg0)

This workflow efficiently extracts a specific key-value pair from a JSON object by using a designated row index. Users input JSON data along with the desired index, and the workflow processes this information to return the exact key-value pair situated at that position. This functionality is particularly beneficial for data analysts and developers who require precise data extraction from complex JSON structures. By automating this process, the workflow reduces manual effort, minimizes errors, and accelerates data handling tasks, providing a seamless solution for streamlined operations.

This n8n workflow is designed to calculate the centroid of a set of vectors presented in a JSON array. It ensures each input vector has consistent dimensions before processing. The calculated centroid is returned as a result, with an error message provided if inconsistencies are detected. This workflow is essential for data analysts dealing with vector data, as it automates the computation, saving time and reducing the likelihood of manual errors. Its implementation benefits those needing to streamline vector analysis in AI data investigations.

This workflow leverages OpenAI to analyze incoming data and generates a personalized WhatsApp link with a preset message. By setting a default country code, users can streamline communication processes, reducing response times and improving efficiency. Ideal for businesses seeking to automate customer interactions and enhance engagement through personalized messaging.

Enhance your data analysis by connecting an AI Agent to your dataset, using n8n tools. This template teaches you how to build an AI Data Analyst Chatbot that is capable of pulling data from your sources, using tools like Google Sheets or databases. It's designed to be easy and efficient, making it a good starting point for AI-driven data analysis. You can easily replace the current Google Sheets tools for databases like Postgres or MySQL. 

This n8n workflow automates the seamless integration of data management and communication by filtering data from Google Sheets, summarizing it with Langchain, and sending the summarized content through Gmail. It enhances efficiency by reducing manual data handling, ensuring timely information dissemination, and allowing users to focus on strategic tasks.

This n8n workflow automates the process of extracting and analyzing survey insights using Qdrant, Python, and an information extractor. It streamlines the data collection and analysis process, enabling efficient management and interpretation of survey data. By integrating these services, users can gain valuable insights quickly and accurately, reducing the time and effort required in manual data handling. Ideal for businesses and researchers seeking to enhance their data-driven decision-making capabilities.

This n8n workflow template creates an HTTP webhook to listen for incoming requests, processes the data using Langchain's AI capabilities, logs the results into Google Sheets, and sends notifications via Gmail. It streamlines data analysis tasks by automating data processing and reporting, providing users with real-time insights and efficient communication channels. This workflow is ideal for businesses seeking to enhance data-driven decision-making and improve operational efficiency.

This n8n workflow template automates the analysis and extraction of Amazon keywords through a webhook mechanism, streamlining the process of keyword research. By automating this task, it significantly reduces manual effort and errors, allowing users to efficiently gather and utilize keyword data for marketing and SEO purposes, enhancing their strategic decision-making capabilities.

The Token Estim8r UI workflow in n8n is designed to streamline the process of tracking and analyzing token usage across various AI models. By fetching execution logs, it extracts token data, calculates costs per run, and sends this information to a backend system for visualization in a UI dashboard. This allows users to efficiently monitor token usage, expenses, and trends, providing valuable insights for cost management and optimization.

This workflow automates the applicant screening process by extracting and analyzing CV data using AI to determine candidate suitability for a specific job role. Results are stored in a Google Sheet, and automated notifications are sent to HR and candidates. It streamlines HR tasks, enhances decision-making quality, and ensures efficient data management.

This workflow automates the extraction and analysis of metadata from marketing images stored in Google Drive using AI. It generates insights like scene context, emotional tone, and SEO keywords. The extracted data is then updated in a Google Sheet, and upon completion, a notification is sent to Slack. This process enhances efficiency by reducing manual effort, ensuring consistent data accuracy, and enabling faster decision-making in marketing campaigns.

The 'Webhook Filter Export Webhook' n8n workflow automates data capture from incoming webhooks, filters the information based on user-defined criteria, and exports the refined data to platforms like Airtable, Google Sheets, or Notion. This workflow ensures efficient data management, reduces manual data sorting, and enhances data accuracy across multiple storage solutions.

This n8n workflow leverages AI to detect workplace discrimination patterns by analyzing data inputs. It integrates services like HTTP and Quickchart to process and visualize data, offering comprehensive insights. Users can identify discrimination trends efficiently, helping organizations foster a fair work environment and ensure compliance with regulations.

The 'Twilio Stickynote Send Triggered' n8n workflow automates the sending of sticky notes through Twilio based on specific conditions set in Airtable. This workflow enhances communication by allowing users to send automated reminders and messages directly from their database, improving response times and productivity. It reduces manual effort, ensuring timely communication, and integrates seamlessly with existing data management processes.

This n8n workflow automates the process of handling web queries and enhances results through semantic re-ranking. It captures data via a webhook, analyzes it for context, and applies intelligent algorithms to prioritize and organize the information. This automation significantly reduces manual effort, improves accuracy, and accelerates data processing, making it invaluable for businesses handling large volumes of web data.

This n8n workflow empowers SQL-based data analysis by integrating OpenAI for natural language processing and Quickchart.io for dynamic data visualization. Users can submit queries in plain language, which the workflow converts into SQL queries to retrieve data from databases like PostgreSQL, MySQL, and SQLite. It then visualizes the retrieved data using Quickchart.io, enhancing the SQL Agent's response with informative charts. This integration streamlines data analysis, making insights more accessible and visually engaging, reducing time spent on manual data interpretation and improving decision-making processes.

This n8n workflow automates the process of analyzing YouTube videos by generating summaries and transcripts, and leveraging Google Gemini AI for enhanced content insights. It streamlines data analysis, making content extraction efficient and accurate. Users benefit from reduced manual effort and improved data accessibility, ideal for content creators and analysts.

# 🚀 **Perfect if you are...** - 💰 **Beginner Investor** – Learn the market faster with AI-powered insights guiding your decisions. - 📈 **Retail Trader** – Optimize your trading strategy with in-depth analysis typically reserved for professionals. - 🏦 **Hedge Fund & Institutional Trader** – Automate high-level market analysis using advanced AI models. - 🤖 **Automation Enthusiast** – Get hands-on with **n8n** and build an automated stock research tool. --- # ❔ **What It Does:** ✅ **AI-Driven Investment Reports** – Our system analyzes **30,000+ tickers** with historical data spanning **30+ years**. It provides **fundamental, technical, and sentiment analysis** in a structured, easy-to-read report. ✅ **Your Personal Hedge Fund on Your PC** – AI-powered advisors analyze **earnings reports, insider trades, stock prices, financial metrics, and news**, delivering precise, data-driven recommendations tailored to you. ✅ **Real Advisors, Real Insights** – Our system replicates the thought processes of **investing legends** like Warren Buffett, Charlie Munger, Cathie Wood, and Ben Graham, offering multiple expert-style perspectives on every stock decision. ✅ **Ultra Low Cost** – Running this workflow costs **less than $0.30 per report** (*AI model costs not included*). That’s cheaper than a cup of coffee, yet it provides insights worth thousands of dollars. --- # 🛠️ **Initial Setup** - Visit [FinancialDatasets.ai](FinancialDatasets.ai) and retrieve your API key. - Locate the **HTTPS Nodes** (🌐) and insert your API key under the header **X-API-KEY** in each one. - In the **Gmail node**, ensure you set up the email where you want to receive your reports. - Test your workflow by typing the name of a company or the stock ticker in the chat. Your report should arrive within 10 minutes. --- # 🧪 **Customize It!** - To modify the **workflow triggers**, change the trigger type and **update the message that the Ticker Extractor receives** in this part of the prompt: `"Based on this message, =={{ $json.chatInput }}== "` *This prevents any disruptions in the workflow.* - To **change the report destination**, update the node type. You can send reports to **Telegram, Slack, or other platforms** instead of Gmail. - Each **advisor's personality** is configured through its system message—feel free to tweak it to suit your needs. - You can **create new agents** by duplicating an existing one and assigning it a different personality. **Remember to reference the new agent in the linked nodes** to ensure seamless integration. ---- ⚠️ **Important Note:** This workflow requires an **API key from [FinancialDatasets.ai](FinancialDatasets.ai)** to access stock market data.

This n8n workflow automates the aggregation process of spreadsheet or table data, focusing on specific columns. By calculating sums or averages, it eliminates the need for manual data entry and analysis, saving time and reducing errors. Ideal for users who handle large datasets, it enhances data-driven decision making and operational efficiency.

This workflow automates the process of extracting data from images using a Webhook and Gemini AI API. It captures image data through a Webhook, processes the data using Gemini AI, and extracts relevant information. This automated solution enhances efficiency by eliminating manual data extraction, reducing errors, and enabling seamless data integration into systems.

The 2006 Filter Manual Automation Webhook workflow is designed to streamline the process of gathering and analyzing company research data with a focus on accuracy and efficiency. By automating the initial collection and filtering of data, it significantly reduces manual effort and minimizes errors. This workflow is particularly valuable for businesses looking to enhance their decision-making processes by providing timely and relevant company insights. It leverages n8n's capabilities to automate repetitive tasks, thus allowing teams to focus on more strategic activities. Additionally, it supports integration with various data sources, ensuring a comprehensive approach to data analysis and research.

This workflow streamlines the process of extracting financial transaction details from Gmail emails and attachments, converting them into structured bookkeeping data using AI, and exporting the results to a Google Sheet. By automating data extraction and organization, it minimizes manual input, reduces errors, and ensures all financial records are promptly and accurately updated.

This workflow leverages n8n to create an HTTP manual automation webhook designed to analyze screenshots using AI technology. It efficiently processes image data, extracting valuable insights by integrating AI-driven analysis tools. Key benefits include enhanced data analysis capabilities, time savings through automation, and improved accuracy in image interpretation, making it vital for businesses seeking to optimize their data workflows.

This n8n workflow facilitates efficient data management by automating the receipt of HTTP requests, data splitting, and interaction with Google Sheets and Langchain for advanced language processing. By integrating AI capabilities, it enhances communication and streamlines processes, making it ideal for businesses looking to improve operational efficiency and data handling accuracy.

This n8n workflow template for customer sentiment analysis automates the evaluation of customer feedback by using AI-powered natural language processing. It efficiently processes text data from various sources to determine sentiment polarity, allowing businesses to quickly gauge customer satisfaction and make data-driven decisions. By streamlining sentiment analysis, this workflow saves time, enhances accuracy, and provides valuable insights into customer opinions, ultimately contributing to improved customer experience and retention strategies.

The 'Aggregate HTTP Create Webhook' workflow in n8n automates the integration of multiple services by harnessing HTTP requests to gather and process data efficiently. It facilitates seamless communication between Langchain tools and Airtable, enhancing data organization and accessibility. This workflow brings significant productivity improvements by automating data collection, reducing manual effort, and ensuring accurate data processing. By automating data interactions, users benefit from streamlined operations and improved efficiency in handling large datasets.

The 'Wait Limit Import Webhook' n8n workflow is designed to efficiently handle and process large volumes of incoming data via webhooks. By splitting and managing these data batches, it ensures that each segment is processed within specified limits, optimizing response times and resource allocation. This results in streamlined data handling, making it invaluable for businesses needing to manage high-frequency data inputs without overloading their systems.

The 'Wait Webhook Process Webhook' workflow acts as a vital bridge for real-time data transmission between disparate systems through HTTP webhooks. It listens for incoming requests, instantly processes the received data, and executes pre-defined actions without manual intervention. This automation enhances efficiency, reduces latency in data handling, and ensures that triggered tasks are executed promptly, making it invaluable for businesses seeking seamless integration and immediate response capabilities.

The 'Wait Splitout Create Webhook' workflow in n8n streamlines data integration from webhooks by parsing and channeling information to various applications such as Google Sheets and Gmail. Leveraging Langchain's AI, it enhances language model processing for better data management and communication, making it a valuable tool for improving efficiency and accuracy in handling large data sets.

The Crop Yield Predictor workflow leverages AI data analysis to estimate crop yields based on various input factors such as weather conditions, soil quality, and historical yield data. By automating data collection and analysis, it provides farmers and agricultural analysts with accurate predictions, helping them optimize resource allocation and improve planning. This workflow enhances decision-making and efficiency in agricultural operations, reducing risks and increasing potential productivity.

The 'Send Triggered' workflow automates user response management by integrating Langchain's sophisticated AI capabilities with memory management and external APIs. This setup ensures prompt and accurate responses based on real-time data, enhancing the quality of user interactions. It is particularly beneficial for businesses looking to streamline customer support operations by utilizing advanced AI for data analysis.

The 'Splitout Code Send Triggered' workflow facilitates the automated extraction and summarization of information from various document sources using Langchain tools. By leveraging AI to retrieve pertinent data from platforms like Wikipedia, the workflow efficiently distills and distributes summarized insights. This automation enhances the speed and accuracy of information processing, enabling users to make informed decisions quickly. It is particularly valuable for businesses that require rapid data analysis and dissemination, optimizing workflows and increasing productivity.

The Machine Downtime Predictor workflow in n8n is designed to analyze machine data and predict potential downtime using AI-driven insights. It integrates seamlessly with existing data sources, processes real-time information, and alerts users to potential issues before they occur. This proactive approach minimizes disruptions, enhances operational efficiency, and reduces maintenance costs by allowing timely interventions. The workflow's capabilities in predictive analysis enable businesses to maintain continuous operations and optimize machine performance.

This n8n workflow template, Script Dialogue Analyzer, leverages AI-driven data analysis to evaluate and interpret dialogues from scripts. It processes input data, applies advanced natural language processing (NLP) algorithms, and generates insightful reports on dialogue dynamics, character interactions, and sentiment analysis. By automating the analysis, it saves time, increases accuracy, and provides valuable insights for writers, editors, and content creators looking to enhance script quality and coherence.

This n8n workflow automates the analysis of hotel reviews by leveraging AI to determine the sentiment behind each review, whether positive, negative, or neutral. By automating the sentiment analysis process, businesses can quickly gain insights into customer satisfaction and identify areas for improvement, enhancing overall service quality. The workflow minimizes manual effort, improves accuracy, and allows for real-time data processing.