AI Automation Workflows — Page 26 | Neura Market
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    • Automate SEO-Optimized Blog Creation with AI and Vector Databases

      This workflow automates the creation of SEO-optimized blog content using n8n, Scrapeless, and Pinecone. It leverages Retrieval-Augmented Generation (RAG) to gather and analyze high-performing content, storing it in a vector database for generating new blog posts.

      n8nFree

    • Automate Multilingual Audio/Video Transcription with ElevenLabs in n8n

      Effortlessly transcribe audio and video files into text across 99+ languages using the ElevenLabs Scribe model in n8n. This workflow automates file uploads, transcription, and text export for various applications.

      n8nFree

    • Create a Reddit Q&A Chatbot Using OpenAI and Reddit API

      This workflow enables you to interact with Reddit posts using a chatbot powered by OpenAI's GPT-4o and the Reddit API. It retrieves posts from a specified subreddit and provides answers to your questions, offering a seamless Q&A experience.

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  1. Automate AI-Powered Lyrics Analysis via Telegram Bot

    Transform your Telegram bot into an AI-driven lyrics assistant that downloads, cleans, and analyzes song lyrics, providing translations, summaries, vocabulary, and more.

    n8nFree

  2. Automate AI Image Generation and Editing with OpenAI and Share via Telegram

    Transform text prompts into stunning images or edit existing visuals using OpenAI's GP-4 Vision model. This n8n workflow automates image creation and editing, stores results in the cloud, and delivers them via Telegram.

    n8nFree

  3. Integrate OpenAI Responses API with n8n for Enhanced AI Workflows

    This n8n workflow enables the integration of OpenAI's Responses API with existing AI workflows, allowing for seamless interaction with LLM and AI Agent nodes. It uses webhooks to intercept and remap requests for compatibility.

    n8nFree

  4. Automate 3D Model and Texture Generation from Images Using Hunyuan3D AI

    This n8n workflow leverages the Replicate API to transform images into 3D models and textures using the ndreca/hunyuan3d-2.1-test AI model. It automates the entire process, from sending requests to retrieving results, ensuring efficient and high-quality 3D content generation.

    n8nFree

  5. Create Personal Data Vector Store from Google Sheets with OpenAI & Gemini AI

    This workflow integrates **Google Sheets** with **Supabase Vector Store** for storing personal data as vectors. It utilizes **OpenAI** and **Google Gemini** AI models for enhanced data processing and querying. The workflow performs the following tasks: - **Extracts personal data** from Google Sheets. - Processes the data using **AI tools** like OpenAI and Google Gemini for intelligent insights. - **Inserts the data** into **Supabase** as vectors, enabling efficient storage and fast querying. - Includes seamless integration with **Postgres** for memory management. - Supports data **loading**, **embedding**, and **management**. This template is ideal for: - Personal data storage with AI-driven **querying** and **analysis**. - Building **intelligent agents** that interact with your data. - Efficient vector-based storage for **personal information**. Perfect for those looking to integrate AI into their personal data workflows.

    n8nFree

  6. AI Privacy-Minded Router: PII Detection for Privacy, Security, & Compliance

    ## Modern AI systems are powerful but pose privacy risks when handling sensitive data. Organizations need AI capabilities while ensuring: - Sensitive data never leaves secure environments - Compliance with regulations (GDPR, HIPAA, PCI, SOX) - Real-time decision making about data sensitivity - Comprehensive audit trails for regulatory review ## The Concept: Intelligent Data Classification + Smart Routing The goal of this concept is to build the foundations of the safe and compliant use of LLMs in Agentic workflows by automatically detecting sensitive data, applying sanitization rules, and intelligently routing requests through secure processing channels. This workflow will analyze the user's chat or webhook input and attempt to detect PII using the Enhanced PII Pattern Detector. If detected, the workflow will process that input via a series of Compliance, Auditing, and Security steps which log and sanitize the request prior to any LLM being pinged. ## Why Multi-tier Routing? Traditional systems use binary decisions (sensitive/not sensitive). Our 3-tier approach provides: - **Granular Security**: Critical PII gets maximum protection - **Performance Optimization**: Clean data gets full cloud capabilities - **Cost Efficiency**: Expensive local processing only when needed - **User Experience**: Maintains conversational flow across security levels ## Why Context-Aware Detection? Regex patterns alone miss contextual sensitivity. Our approach: - **Catches Intent**: Bank account discussion is sensitive even without account numbers - **Reduces False Negatives**: Medical discussions stay secure even without explicit medical IDs - **Proactive Protection**: Identifies sensitive contexts before PII is shared - **Compliance Alignment**: Matches how regulations actually define sensitive data ## Why Risk Scoring vs Binary Classification? Binary PII detection creates artificial boundaries. Risk scoring provides: - **Nuanced Decisions**: Multiple low-risk patterns might aggregate to high risk - **Adaptive Thresholds**: Organizations can adjust sensitivity based on their needs - **Better UX**: Users aren't unnecessarily restricted for low-risk scenarios - **Audit Transparency**: Clear reasoning for every routing decision ## Why Comprehensive Monitoring? Privacy systems require trust and verification: - **Compliance Proof**: Audit trails demonstrate regulatory compliance - **Performance Optimization**: Identify bottlenecks and improve efficiency - **Security Validation**: Ensure no sensitive data leakage occurs - **Operational Insights**: Understand usage patterns and system health ## How to Install: All that you will need for this workflow are credentials for your LLM providers such as Ollama, OpenRouter, OpenAI, Anthropic, etc. This workflow is customizable and allows the user to define the best LLM and storage/memory solutions for their specific use case.

    n8nFree

  7. Generate Images with GP-image-1 and Store in Google Drive with Cost Tracking

    ## How it works - Receive a chat input as an image prompt. - Call OpenAI's `gpt-image-1` API to generate an image. - Split the returned images and process them one by one. - Upload each generated image to **Google Drive**. - Save image links and thumbnails to a **Google Sheets** document. - Record token usage and estimated cost into a separate sheet. ## Set up steps 1. Connect your **OpenAI API** credentials for image generation. 2. Connect your **Google Drive** and **Google Sheets** accounts. 3. Set the destination folder in Google Drive. 4. Set the target Google Sheet and specify the correct sheet tabs. 5. The setup usually takes around **5-10 minutes**. 6. Detailed field mappings are already pre-configured inside the workflow. 7. Additional tips and instructions are included as **sticky notes** inside the workflow. ![Screenshot_20250425_190410_NRnD1vZE2x 2.jpg](fileId:1166) ## Google Sheet copy URL [Copy Sheet Link](https://docs.google.com/spreadsheets/d/1zsWBgeA7I5Q_gsocz6hmkW884Q_vfz_mgGC54VSN0/copy)

    n8nFree

  8. Transform Gmail Emails into Vector Embeddings with PGVector and Ollama

    Automatically convert Gmail emails into vector embeddings using PGVector and Ollama for advanced semantic searches and data analysis.

    n8nFree

  9. Automate Image Creation and Editing with OpenAI's GPT-Image-1

    Leverage OpenAI's GPT-Image-1 model to automate the generation and editing of images based on custom prompts. Ideal for creative workflows in marketing, design, and product visualization.

    n8nFree

  10. Automate Video Transcription and Blog Research with AI and Google Sheets

    This workflow automates the process of converting uploaded videos into structured blog research. It transcribes videos, extracts keywords, performs competitor research, and organizes the findings in Google Sheets using Dumpling AI and OpenAI.

    n8nFree

  11. Create a Conversational WhatsApp AI Assistant with Memory Using Gemini AI and Pinecone

    This workflow sets up an intelligent AI assistant for WhatsApp that responds naturally using Google Gemini AI, remembers past conversations, and accesses a knowledge base for FAQs. It leverages Pinecone for memory storage and OpenAI for embeddings.

    n8nFree

  12. Automate Startup Idea Generation from Reddit Discussions

    This workflow automates the discovery of startup ideas by scraping Reddit posts for unmet needs, analyzing them with Gemini AI, and storing insights in Google Sheets.

    n8nFree

  13. Generate Dynamic JSON Output Formats for AI Agents with Mistral

    This workflow contains community nodes that are only compatible with the self-hosted version of n8n. # JSON Architect - Dynamically Generate JSON Output Formats for Any AI Agent ## Overview Version: 1.0 The JSON Architect Workflow is designed to instruct AI agents on the required JSON structure for a given context and create the appropriate JSON output format. This workflow ensures that the generated JSON is validated and tested, providing a reliable JSON output format for use in various applications. ## Features - **Dynamic JSON Generation**: Automatically generate the JSON format based on the input requirements. - **Validation and Testing**: Validate the generated JSON format and test its functionality, ensuring reliability before output. - **Iterative Improvement**: If the generated JSON is invalid or fails testing, the workflow will attempt to regenerate it until successful or until a defined maximum number of rounds is reached. - **Structured Output**: The final output is the generated JSON output format, making it easy to integrate with other systems or workflows. ## Who is this for? This workflow is ideal for developers, data scientists, and businesses that require dynamic JSON structures for the responses of AI agents. It is particularly useful for those involved in procedural generation, data interchange formats, configuration management, and machine learning model input/output. ## What problem does this solve? The workflow addresses the challenge of generating optimal JSON structures by automating the process of creation, validation, and testing. This approach ensures that the JSON format is appropriate for its intended use, reducing errors and enhancing the overall quality of data interchange. Use-Case examples: - Data Interchange Formats - Procedural Generation - Machine Learning Model Input/Output - Configuration Management ## What this workflow does The workflow orchestrates a process where AI agents generate, validate, and test JSON output formats based on the provided input. This approach leads to a more refined and functional JSON output parser. ## Workflow Steps 1. **Input & Setup**: The initial input is provided, and the workflow is configured with necessary parameters. 2. **Round Start**: Initiates the round of JSON construction, ensuring the input is as expected. 3. **JSON Generation & Validation**: Generates and validates the JSON output format according to the input. 4. **JSON Test**: Verifies whether the generated JSON output format works as intended. 5. **Validation or Test Fails**: If the JSON fails validation or testing, the process loops back to the **Round Start** for correction. 6. **Final Output**: The final output is generated based on successful JSON construction, providing a cohesive response. ## Expected Input - **input**: The input that requires a proper JSON structure. - **max_rounds**: The maximum number of rounds before stopping the loop if it fails to produce and test a valid JSON structure. Suggested: 10. - **rounds**: The initial number of rounds. Default: 0. ### Expected Output - **input**: The original input used to create the JSON structure. - **json_format_name**: A snake_case identifier for the generated JSON format. Useful if you plan to reuse it for multiple AI agents or Workflows. - **json_format_usage**: A description of how to use the JSON output format in an input. Meant to be used by AI agents receiving the JSON output format in their output parser. - **json_format_valid_reason**: The reason provided by the AI agents explaining why this JSON format works for the input. - **json_format_structure**: The JSON format itself, intended for application through the **Advanced JSON Output Parser** custom node. - **json_format_input**: The **input** after the JSON output format (**json_format_structure**) has been applied in an AI agent's output parser. ## Example ![printscreen1.png](fileId:1728) ![printscreen9.png](fileId:1729) ![printscreen11.png](fileId:1730) An example that includes both the input and the final output is provided in a note within the workflow. ### n8n Setup Used - **n8n Version**: 1.100.1 - **n8n-nodes-advanced-output-parser**: 1.0.1 - **Running n8n via**: Podman 4.3.1 - **Operating System**: Linux ## Requirements to Use/Setup ### Credentials & Configuration - Obtain the necessary LLM API key and permissions to utilize the workflow effectively. - This workflow is dependent on a custom node for dynamically inputting JSON output formats called **n8n-nodes-advanced-output-parser**. You can find the repository [here](https://github.com/volkovmqx/n8n-nodes-advanced-output-parser). *Warning: As of 2025-07-09, the custom node creator has warned that this node is not production-ready. Beware when using it in production environments without being aware of its readiness.* ## Notes, Assumptions & Warnings - This workflow assumes that users have a basic understanding of n8n and JSON.

    n8nFree

  14. Automate LinkedIn Profile Discovery and Cold Email Outreach

    Streamline your LinkedIn profile searches and cold email outreach by automating the process with n8n, OpenAI, and Hunter. This workflow saves time by generating contact details and context from LinkedIn profiles, allowing for efficient communication with potential candidates or clients.

    n8nFree

  15. Automate Research Report Generation with Jina AI and Google Gemini

    Transform a research question into a comprehensive, well-cited report using Jina AI for web crawling and Google Gemini for advanced summarization and report generation.

    n8nFree

  16. Automate AI Image Generation and Upload to WordPress and Twitter

    This workflow generates AI images from text prompts using Leonardo AI, uploads them to WordPress, and prepares them for posting on Twitter. Ideal for automating visual content creation for blogs and social media.

    n8nFree

  17. Transform Telegram Messages into AI-Generated Images with DALL·E and GPT

    This n8n workflow automates the conversion of text prompts sent via Telegram into high-quality AI-generated images using OpenAI's DALL·E and GPT models.

    n8nFree

  18. Automate YouTube Video Summaries to Telegram Using GPT-4

    Streamline your information intake by automatically transcribing and summarizing YouTube videos, then delivering concise summaries to Telegram using GPT-4.

    n8nFree

  19. Automate Translation and Publishing of RSS Feed Content to WordPress in Hindi

    This workflow automates the process of translating RSS feed articles from English to Hindi using OpenAI and publishes them as draft posts on WordPress, complete with featured images.

    n8nFree

  20. Generate SWOT Analysis Reports with OpenAI, Google Sheets & API Template PDF Export

    ### SWOT Analysis Generator that Produces PDF Reports In n8n Want to skip the manual work and instantly generate SWOT analyses for your business plans, investor decks, or strategy docs? This workflow lets you automate the entire SWOT (Strengths, Weaknesses, Opportunities, Threats) process—using AI and no-code tools! Whether you're using this for yourself or creating documents for clients, this workflow will save you hours of time and help identify the key components of growing any business. #### Tools We'll Be Using: - **OpenAI API**: Powers AI-driven extraction and generation of SWOT sections, introductions, conclusions, and more. - **n8n**: The no-code automation platform that orchestrates this workflow. - **Google Sheets**: Stores your company data and report outputs (download the provided SWOT Analysis template and fill it out). - **APItemplate.io**: Converts HTML reports into downloadable, multi-page PDFs. - **DeepSeek API** *(optional)*: An alternative to OpenAI for specific reasoning tasks. - **Gmail OAuth2**: Sends the final report via email. If you're building a business, doing client work, or just want faster strategic planning—this will save you HOURS. --- ### How It Works This n8n workflow transforms structured company data from a Google Sheet into a fully formatted, investor-grade SWOT report in both HTML and PDF formats. Here's the process in a few high-level steps: 1. **Load Data**: Pulls company information from the Company Info Input tab in the SWOT Analysis Google Sheet. 2. **AI Analysis**: Uses AI (via OpenAI or DeepSeek) to categorize data into Strengths, Weaknesses, Opportunities, and Threats, and generates detailed narrative sections for each. 3. **Create Report Sections**: Produces a strategic introduction, conclusion, table of contents, and title page using AI. 4. **Format and Combine**: Converts all sections into styled HTML and merges them into a single document. 5. **Generate PDF**: Converts the HTML into a polished, multi-page PDF using APItemplate.io. 6. **Save and Share**: Saves the report back to Google Sheets and emails the PDF to a specified recipient. The result is a professional, investor-ready SWOT report with minimal manual effort, ready for sharing or review. --- ### Setup Steps Setting up this workflow typically takes **15-30 minutes**, depending on your familiarity with the tools. Here's what you'll need to do: - **Configure Credentials**: Set up API keys and OAuth2 credentials for Google Sheets, OpenAI, APItemplate.io, Gmail, and optionally DeepSeek. - **Prepare Your Google Sheet**: Download the provided SWOT Analysis template, fill out the Company Info Input tab with your company data, and ensure it's accessible. - **Import the Workflow**: Copy the workflow JSON into your n8n instance and connect your credentials. **Detailed instructions** for each step, including credential setup and customization options, are available in the sticky notes within the workflow. Refer to these for step-by-step guidance. --- ### Benefits - **Efficiency**: Automates the entire SWOT report generation process, saving hours of manual work. - **Professional Output**: Delivers fully styled HTML and PDF reports with headings, paragraphs, and custom layouts. - **AI-Driven Insights**: Ensures clarity and relevance in every section through targeted AI analysis. - **Seamless Sharing**: Automatically saves reports to Google Sheets and emails them to stakeholders. This workflow is perfect for entrepreneurs, consultants, or strategists looking to streamline their SWOT analysis process and deliver high-quality, professional reports effortlessly.

    n8nFree

  21. Transcribe YouTube Videos with AI Enhancement via Chat Interface

    ## About: This workflow automates the transcription of YouTube videos by processing a video URL provided via a chat message. Designed for users who need quick access to video content in text form, this workflow ensures a seamless experience for transcribing videos on demand, regardless of the topic. ## Who is this for? This workflow is designed for individuals who need quick and accurate transcriptions of YouTube videos without watching them in full. It is particularly useful for: - Students who need text-based notes from educational videos. - Researchers looking to extract information from lectures or discussions. - Professionals who prefer reading over watching videos. - Casual users who want an efficient way to summarize video content. ## What problem is this workflow solving? Manually transcribing YouTube videos is time-consuming and prone to errors. Watching long videos just to extract key information is inefficient. This workflow automates transcription, allowing users to quickly convert video content into text. Use cases include: - Summarizing lectures or webinars. - Extracting insights from interviews and discussions. - Creating searchable text from video content. - Generating reference material without watching entire videos. ## What This Workflow Does? This workflow automates the transcription of YouTube videos by: 1. **Accepting Input:** Users provide a YouTube video URL through a chat message. 2. **Processing the Video:** It utilizes an external transcription service to retrieve the full transcript of the YouTube video from the provided URL. 3. **Enhancing Output:** An AI model (OpenAI) refines the transcription for accuracy and readability. 4. **Delivering Results:** The final text transcript is returned to the user via the chat interface. ## Setup: 1. **Install n8n:** Ensure you have n8n installed and running. 2. **Import the Workflow:** Copy the JSON workflow file into your n8n instance. 3. **Configure API Keys:** - Set up your Supadata ([Supadata](https://supadata.ai)) API key for transcription. - Configure the OpenAI ([OpenAI](https://platform.openai.com/api-keys)) API key for additional processing. 4. **Run the Workflow:** Provide a YouTube video URL and receive a transcription in response. ## How to customize this workflow to your needs: The workflow is flexible and can be tailored to suit specific requirements. Here are some customization ideas: - **Language Support:** Adjust the transcription language in both the HTTP Request and OpenAI nodes to support transcriptions in different languages (e.g., French, German). - **Integrate with Other Services:** Store transcriptions in a database, send them via email, or connect with a document management system. - **Notification:** Add a notification node (e.g., email or Slack) to alert you when the transcription is complete, especially for long videos. - **Quality Check:** Integrate an additional AI step to summarize or highlight key points in the transcript for quicker insights. This workflow is designed to be scalable, efficient, and adaptable to various transcription needs. ## Limitations - **Video Length Limitation:** Very long videos may not have a complete transcription due to constraints in processing capacity or service limitations. - **Transcription Dependency:** The accuracy of the transcription relies entirely on the presence of video captions or subtitles. If a video lacks these, no transcription will be generated. - **Access Restrictions:** Private or restricted YouTube videos may not be accessible for transcription due to permission limitations. - **Processing Time:** The time required to process a video can vary significantly, especially for longer videos, depending on the transcription service and server resources. - **Regional Restrictions:** Some YouTube videos may have geographic or regional access limitations, which could prevent the workflow from retrieving the content for transcription.

    n8nFree
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