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.