OpenAI Automation Workflows
899 ready-made OpenAI workflows for n8n, Make, Zapier, Activepieces, and Pipedream. GPT-powered enrichment, generation, and classification inside your automations.
Intelligent Chatbot with OpenAI, PostgreSQL Memory, and API Integration
This workflow creates an intelligent chatbot using OpenAI, integrated with PostgreSQL for memory retention and API calling capabilities, designed to enhance customer interactions via WhatsApp Business.
n8n$9.99Automate Image Analysis and Feedback in Telegram Using OpenAI
This workflow automates the process of analyzing images received via Telegram and provides insightful feedback using OpenAI, enhancing communication and moderation in Telegram groups.
n8n$4.99Automate Data Analysis from Google Sheets Using OpenAI
Leverage OpenAI to automatically analyze data from Google Sheets, providing insights and key performance indicators (KPIs) with ease.
n8n$4.99Automate Real Estate Listing Revivals with OpenAI and Gmail
This workflow automates the process of reviving expired real estate listings by sending personalized follow-up emails using OpenAI and Gmail, ensuring no potential leads are missed.
n8n$4.99Transform Press Releases (PDF & Word) into Polished Articles with Gmail & OpenAI
This n8n workflow automates the transformation of press releases into polished articles. It converts the content of an email and its attachments (PDF or Word documents) into an AI-written article/blog post. ## What does it do? This workflow assists editors and journalists in managing incoming press releases from governments, companies, NGOs, or individuals. The result is a draft article that can easily be reviewed by the editor, who receives it in a reply email containing both the original input and the output, plus an AI-generated self-assessment. This self-assessment represents an additional feedback loop where the AI compares the input with the output to evaluate the quality and accuracy of its transformation. ## How does it work? Triggered by incoming emails in Gmail, it first filters attachments, retaining only Word and PDF files while removing other formats like JPGs. The workflow then follows one of three paths: - If no attachments remain, it processes the inline email message directly. - For PDF attachments, it uses an extractor to obtain the document content. - For Word attachments, it extracts the text content by an HTTP request. In each case, the extracted content is then passed to an AI agent that converts the press release into a well-structured article according to predefined prompts. A separate AI evaluation step provides a self-assessment by comparing the output with the original input to ensure quality and accuracy. Finally, the workflow generates a reply email to the sender containing three components: the original input, the AI-generated article, and the self-assessment. This streamlined process helps editors and journalists efficiently manage incoming press releases, delivering draft articles that require minimal additional editing. ## How to set it up ### 1. Configure Gmail Connection: - Create or use an existing Gmail address - Connect it through the n8n credentials manager - Configure polling frequency according to your needs - Set the trigger event to Message Received Optional: Filter incoming emails by specifying authorized senders - Enable the Download Attachments option ### 2. Set Up AI Integration: - Create an OpenAI account if you don't have one - Create a new AI assistant or use an existing one - Customize the assistant with specific instructions, style guidelines, or response templates - Configure your API credentials in n8n to enable the connection ### 3. Configure Google Drive Integration: - Connect your Google Drive credentials in n8n - Set the operation mode to Upload - Configure the input data field name as data - Set the file naming format to dynamic: {{ $json.fileName }} ### 4. Configure HTTP Request Node: - Set request method to POST - Enter the appropriate Google API endpoint URL - Include all required authorization headers - Structure the request body according to API specifications - Ensure proper error handling for API responses ### 5. Configure HTTP Request Node 2: - Set request method to GET - Enter the appropriate Google API endpoint URL - Include all required authorization headers - Configure query parameters as needed - Implement response validation and error handling ### 6. Configure Self-Assessment Node: - Set operation to Message a Model - Select an appropriate AI model (e.g., GPT-4, Claude) - Configure the following prompt in the Message field: Please analyze and compare the following input and output content: (for example) Original Input: {{ $(HTTP Request3).item.json.data }} {{ $(Gmail Trigger).item.json.text }} Generated Output: {{ $json.output }} Provide a detailed self-assessment that evaluates: 1. Content accuracy and completeness 2. Structure and readability improvements 3. Tone and style appropriateness 4. Any information that may have been omitted or misrepresented 5. Overall quality of the transformation ### 7. Configure Reply Email Node: - Set operation to Send and select your Gmail account - Configure the to field to respond to the original sender: {{ $(Gmail Trigger).item.json.from }} - Set an appropriate subject line: RE: {{ $(Gmail Trigger).item.json.subject }} - Structure the email body with clear sections using the following template: ``` handlebars **EDITED ARTICLE** {{ $(AI Article Writer 2).item.json.output }} **SELF-ASSESSMENT** Rating: 1 (poor) to 5 (excellent) {{ $json.message.content }} **ORIGINAL MESSAGE** {{ $(Gmail Trigger).item.json.text }} **ATTACHMENT CONTENT** {{ $(HTTP Request3).item.json.data }} ``` Note: Adjust the template fields according to the input source (PDF, Word document, or inline message). For inline messages, you may not need the ATTACHMENT CONTENT section.
n8n$14.99Automate Gmail Email Categorization Using OpenAI GPT-4
Streamline your Gmail inbox management by automatically categorizing emails based on content intent using OpenAI's GPT-4. This workflow helps prioritize important messages and improves productivity for teams handling high email volumes.
n8n$14.99Evaluate AI Agent Response Correctness with OpenAI and RAGAS Methodology
### This n8n template demonstrates how to calculate the evaluation metric Correctness which in this scenario, measures, compares, and classifies the agent's response against a set of ground truths. The scoring approach is adapted from the open-source evaluations project [RAGAS](https://docs.ragas.io/) and you can see the source here [https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py](https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py) ### How it works - This evaluation works best where the agent's response is allowed to be more verbose and conversational. - For our scoring, we classify the agent's response into 3 buckets: True Positive (in answer and ground truth), False Positive (in answer but not in ground truth), and False Negative (not in answer but in ground truth). - We also calculate an average similarity score on the agent's response against all ground truths. - The classification and the similarity score are then averaged to give the final score. - A high score indicates the agent is accurate, whereas a low score could indicate the agent has incorrect training data or is not providing a comprehensive enough answer. ### Requirements - n8n version 1.94+ - Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)
n8n$14.99Real-time Sales Pipeline Analytics with Bright Data, OpenAI, and Google Sheets
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically tracks key sales pipeline metrics—new leads, deal stages, win rates—and sends actionable insights to your team. Eliminate manual CRM exports and stay on top of revenue health. ## Overview The automation queries your CRM API (HubSpot, Salesforce, or Pipedrive) on a schedule, pulls pipeline data, and feeds it into OpenAI for anomaly detection (e.g., stalled deals). Summaries and alerts appear in Slack, while daily snapshots are archived in Google Sheets for trend analysis. ## Tools Used - **n8n** - Pipeline orchestration - **CRM API** - Connects to your chosen CRM - **OpenAI** - Detects anomalies and highlights risks - **Slack** - Notifies reps and managers in real time - **Google Sheets** - Stores historical pipeline data ## How to Install 1. **Import the Workflow** into n8n. 2. **Connect Your CRM**: Provide API credentials in the HTTP Request node. 3. **Set Up OpenAI**: Add your API key. 4. **Authorize Slack & Google Sheets**. 5. **Customize Thresholds**: Adjust what constitutes a stalled deal or low conversion. ## Use Cases - **Sales Management**: Monitor pipeline health without dashboards. - **Revenue Operations**: Detect bottlenecks early. - **Forecasting**: Use historical snapshots to improve predictions. - **Rep Coaching**: Alert reps when deals stagnate. ## Connect with Me - **Website**: https://www.nofluff.online - **YouTube**: https://www.youtube.com/@YaronBeen/videos - **LinkedIn**: https://www.linkedin.com/in/yaronbeen/ - **Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #salespipeline #crm #openai #slackalerts #n8nworkflow #nocode #revenueops
n8n$14.99Automate AI News Curation from TechCrunch to Slack Using OpenAI
This n8n workflow automatically scrapes TechCrunch articles, filters for AI-related content using OpenAI, and delivers curated summaries to your Slack channels. Ideal for teams needing up-to-date AI industry insights without manual browsing.
n8n$9.99Automate LinkedIn AI News Posts with NewsAPI and OpenAI
This workflow automates the creation and publication of LinkedIn posts about trending AI news. It fetches news articles using NewsAPI, enhances content with Qdrant, and generates professional posts using OpenAI's GPT-4o-mini model.
n8n$14.99Evaluate RAG Response Accuracy with OpenAI: Document Groundedness Metric
### This n8n template demonstrates how to calculate the evaluation metric RAG document groundedness, which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents. The scoring approach is adapted from [https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness](https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness) ### How it works - This evaluation works best for an agent that requires document retrieval from a vector store or similar source. - For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to assess if the former is based off the latter. - A key factor is to look out for information in the response which is not mentioned in the documents. - A high score indicates LLM adherence and alignment, whereas a low score could signal inadequate prompt or model hallucination. ### Requirements - n8n version 1.94+ - Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)
n8n$14.99Automate Brand Mention Tracking and Sentiment Analysis with Bright Data and OpenAI
This workflow automates the tracking of brand mentions across online platforms by scraping blog posts and articles. It uses Bright Data for content access and OpenAI for sentiment analysis, saving time and providing insights into brand perception.
n8n$9.99Import Google Keep Notes to Google Sheets Using OpenAI and Google Drive
This n8n workflow automates the import of your Google Keep notes into a structured Google Sheet, using Google Drive, OpenAI for AI-powered processing, and JSON file extraction. It's perfect for users who want to turn exported Keep notes into a searchable, filterable spreadsheet - optionally enhanced by AI summarization or transformation. ## Who is this for? - Researchers, knowledge workers, and digital minimalists who rely on Google Keep and want to better organize or analyze their notes. - Anyone who regularly exports Google Keep notes and wants a clean, automated workflow to store them in Google Sheets. - Users looking to apply AI to process, summarize, or extract insights from raw notes. ## What problem is this workflow solving? Exporting Google Keep notes via Google Takeout gives you unstructured .json files that are hard to read and manage. This workflow solves that by: - Filtering relevant .json files - Extracting note content - (Optionally) applying AI to analyze or summarize each note - Writing the result into a structured Google Sheet ## What this workflow does 1. Google Drive Search: Looks for .json files inside a specified Keep folder. 2. Loop: Processes files in batches of 10. 3. File Filtering: Filters by .json extension. 4. Download + Extract: Downloads each file and extracts note content from JSON. 5. Optional Filtering: Only keeps non-archived notes or those meeting content criteria. 6. AI Processing (optional): Uses OpenAI to summarize or transform the note content. 7. Prepare for Export: Maps note fields to be written. 8. Google Sheets: Appends or updates the target sheet with the note data. ## Setup - Export your Google Keep notes using Google Takeout: - Deselect all, then choose only Google Keep. - Choose "Send download link via email". - Unzip the downloaded archive and upload the .json files to your Google Drive. - Connect Google Drive, OpenAI, and Google Sheets in n8n. - Set the correct folder path for your notes in the “Search in ‘Keep’ folder” node. - Point the Google Sheet node to your spreadsheet ## How to customize this workflow to your needs Skip AI processing: If you don't need summaries or transformations, remove or disable the OpenAI Chat Model node. Filter criteria: Customize the Filter node to extract only recent notes, or those containing specific keywords. AI prompts: Edit the Tools Agent or Chat Model node to instruct the AI to summarize, extract tasks, categorize notes, etc. Field mapping: Adjust the “Set fields for export” node to control what gets written to the spreadsheet. Use this template to build a powerful knowledge extraction tool from your Google Keep archive - ideal for backups, audits, or data-driven insights.
n8n$14.99Automate Client FAQs with RAG Using Google Drive and Azure OpenAI
Create an AI-driven FAQ system using Retrieval-Augmented Generation (RAG) to provide precise answers from Google Drive PDFs via Azure OpenAI. This workflow automates the process of handling client inquiries by extracting relevant information from stored documents.
n8n$14.99Automate LinkedIn Candidate Sourcing with Google X-Ray and OpenAI
Streamline your recruitment process by automatically generating and executing LinkedIn Boolean searches using OpenAI and Google X-Ray, storing results in Google Sheets.
n8n$14.99Automate SEO-Optimized Blog Posts on Blogger with OpenAI and DALL-E
This n8n workflow automates the creation and publishing of SEO-optimized blog posts to Blogger. By sending a blog title via Telegram, it generates comprehensive articles with custom images and publishes them with proper SEO structure.
n8n$14.99AI-Driven Document Interaction Using Nextcloud and OpenAI
This workflow enables AI-powered interactions with documents stored in Nextcloud, utilizing LangChain and OpenAI to answer user queries based on document content.
n8n$14.99Tax Code Assistant with Qdrant, Mistral.ai & OpenAI
Creates an AI-powered knowledge base assistant for tax code documents using intelligent chunking into chapters/sections, Qdrant vector store, and advanced querying via Mistral.ai and OpenAI.
n8n$24.99Automate Tool Execution via Chat with Bright Data MCP and OpenAI
This workflow enables users to trigger and execute Bright Data MCP tools through natural language chat inputs, leveraging OpenAI for intent classification and tool matching.
n8n$14.99Enhance WordPress User Experience with AI Chatbot Using Supabase and OpenAI
This workflow integrates WordPress content with Supabase and OpenAI to create an AI chatbot that enhances user experience through Retrieval-Augmented Generation (RAG).
n8n$19.99Interactive AI Chat with Google Search Console Data via OpenAI and Postgres
This workflow enables interactive communication with your Google Search Console data using an AI agent powered by OpenAI and Postgres. It facilitates natural language queries and retrieves data in a user-friendly chat interface.
n8n$14.99Voice-Powered AI Marketing Assistant with OpenAI & ElevenLabs
Gwen is an intelligent n8n AI agent that generates voice-optimized blog posts, AI images, edits visuals, and delivers natural voice responses using OpenAI and ElevenLabs.
n8n$24.99OpenAI Personal Shopper with RAG and WooCommerce
This workflow integrates OpenAI's chat capabilities with WooCommerce for personalized shopping experiences.
n8n$14.99Create a Dynamic AI Website Assistant with Pinecone and OpenAI
This workflow sets up an AI-driven virtual assistant that dynamically responds to website queries using Pinecone vector search and OpenAI models, with routing based on the source website.
n8n$19.99
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