OpenAI Automation Workflows
899 ready-made OpenAI workflows for n8n, Make, Zapier, Activepieces, and Pipedream. GPT-powered enrichment, generation, and classification inside your automations.
Automate HR Policy Retrieval via Slack with S3 and OpenAI Integration
Enhance your HR support by automating policy retrieval through Slack, utilizing Amazon S3 for document storage and OpenAI for intelligent responses.
n8n$14.99Integrate OpenAI with Notion for an Embeddable Knowledge Base Chatbot
Create an AI-powered chatbot using OpenAI and Notion to serve as a dynamic knowledge base, easily embeddable on your website for customer support.
n8n$9.99Automate Real-time Job and Salary Data Extraction with Bright Data MCP and OpenAI
Streamline the extraction and analysis of job descriptions and salary details from job listings using Bright Data MCP and OpenAI. Ideal for recruiters, HR teams, and market analysts seeking to automate data collection and analysis.
n8n$14.99Parallel LLM Evaluation on Legal Documents with Google Sheets and OpenAI
Efficiently benchmark multiple LLMs on legal documents using Google Sheets and OpenAI, leveraging parallel processing for faster results.
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$14.99Summarize Your Emails with AI (via OpenAI) and Send to Line Messenger
## Who is this template for? - Anyone who is drowning in emails - Busy parents who have a lot of school emails - Busy executives with too many emails  ## Case Study I get too many emails from my kids' school about soccer practice, lunch orders, and parent events. I use this workflow to read all the emails and tell me what is important and what requires actioning. [Youtube tutorial](https://www.youtube.com/watch?v=c1ZcCnca7PM) ## What this workflow does 1. It uses IMAP to read the emails from your email account (i.e., Gmail). 2. It then passes the email to Openrouter.ai and uses a free A.I. model to read and summarize the email. 3. It then sends the summary as a message to your messenger (i.e., Line). ## Setup 1. You need to find your email server IMAP credentials. 2. Input your openrouter.ai API credentials or replace the HTTP request node with an A.I. node such as OpenAI. 3. Input your messenger credentials. I use Line, but you can change the node to another messenger like Telegram. 4. You need to change the message ID to your ID inside the HTTP request. You can find your user ID inside the https://developers.line.biz/console/. Change the to: {insert your user ID}. ## How to adjust it to your needs - You can change the A.I. prompt to fit your needs by telling it to mark emails from a certain address as important. - You can change the A.I. model from the current meta-llama/llama-3.1-70b-instruct:free to a paid model or other free models. - You can change the messenger node to Telegram or any other messenger app you like.
n8n$9.99Automate ClickUp Task Management via Telegram and OpenAI
Streamline your task management by using a Telegram bot to create, update, and delete ClickUp tasks through natural language commands interpreted by OpenAI.
n8n$9.99Automate LinkedIn Posts Using Notion and OpenAI
Streamline your LinkedIn content creation by automating post generation with Notion and OpenAI. This workflow fetches pre-written content from Notion, enhances it using OpenAI, and posts it on LinkedIn.
n8n$9.99Automate Resume Screening and Follow-up Emails with OpenAI, Google Sheets, and Gmail
This workflow automates the process of screening resumes using AI, logging results to Google Sheets, and sending follow-up emails via Gmail. It streamlines HR tasks by evaluating candidate qualifications and fit, then categorizing them for further action.
n8n$9.99Generate LinkedIn Posts from Books Using OpenAI, LangChain & Pinecone Vector Search
Automates the process of generating, storing, and publishing engaging LinkedIn posts derived from books (PDFs) using AI and vector search. --- ## Overview This workflow: 1. **Watches a Google Drive folder** for new or updated book PDFs. 2. **Extracts and embeds** the content using OpenAI. 3. **Stores the data** in a Pinecone vector database. 4. **Uses a LangChain agent** to generate post ideas. 5. **Creates concise LinkedIn posts** with hook, insight, CTA. 6. **Updates a Google Sheet** and posts to LinkedIn. --- ## Workflow Breakdown ### 1. Google Drive Trigger - **Trigger:** Watches a folder for new or updated PDF files. - **Action:** Downloads the updated PDF. ### 2. Extract and Embed Content - **Extract from File:** Parses PDF to extract text. - **Text Splitter:** Breaks text into chunks. - **Embeddings (OpenAI):** Converts chunks into vector embeddings. - **Pinecone Vector Store:** Saves the embeddings with the book name as namespace. ### 3. Post Idea Generation (LangChain Agent) - Uses a prompt to: - Search Pinecone DB - Extract insights - Format into 5 LinkedIn post ideas with: - **Hook** - **Insight** - **CTA** - **Memory buffer** and structured output parser are used for clean AI interaction. ### 4. Post Creation - Each idea is: - **Split** - Rewritten with a GPT model prompt to match LinkedIn tone - Styled for under 600 characters - Includes emojis, hashtags, and tone guidelines ### 5. Google Sheet Integration - Saves all generated posts to a **Google Sheet**. - Marks status: `published` or `no`. ### 6. Scheduled Publishing - Every day: - Pulls an unpublished post - Publishes it to LinkedIn - Updates the post's status and timestamp in the Google Sheet --- ## Setup Guide ### Google Drive - Create a folder for book PDFs - Connect your Google Drive account to n8n - Provide access token with file read permission ### Google Sheets - Create a Google Sheet with columns: - `bookname`, `hook`, `insight`, `cta`, `postContent`, `published`, `date` - Add credentials in n8n with read/write permission ### Pinecone - Set up a Pinecone project and index (`linkedinpost`) - Namespace will be auto-named using the book filename ### API Credentials Required - **OpenAI API** (for embeddings and post generation) - **Pinecone API** (for vector storage and retrieval) - **LinkedIn OAuth2** (to publish posts) - **Google Drive & Sheets** credentials --- ## Flow Summary ```mermaid graph D A[Google Drive Trigger] --> B[Download PDF] B --> C[Extract Text] C --> D[Text Splitter] D --> E[Create Embeddings] E --> F[Pinecone Vector Store] F --> G[LangChain Agent] G --> H[Structured Output (5 Post Ideas)] H --> I[Split Ideas] I --> J[Format as LinkedIn Post (GPT)] J --> K[Store in Google Sheet] L[Schedule Trigger] --> M[Get Unpublished Post] M --> N[Post to LinkedIn] N --> O[Mark as Published] ``` --- ## Prompt Example (Used in LangChain Agent) ```text You are a content strategist. Search the Pinecone vector DB containing a book. Generate 5 unique LinkedIn post ideas with: - A Hook (curiosity driven) - Insight (summary < 100 words) - CTA (Agree or disagree?, etc.) Respond in structured JSON: [ { "Hook": ..., "Insight": ..., "CTA": ... }, ... ] ``` --- ## Output Sample ```json { "Hook": "Why your lab's results might be invalid ±", "Insight": "ISO/IEC 17025 stresses that labs must plan and address risks to impartiality and validity.", "CTA": "Does your lab audit for these risks?" } ``` --- ## Schedule Control - Uses **Schedule Trigger** to post daily at a set time. - Ensures automation with LinkedIn and accurate Google Sheet syncing. --- ## Notes - Posts remain **professional and concise** for a LinkedIn audience. - Works with **any PDF book**. - Supports multi-book pipelines. - You can filter and tag books by filename or folder for segmenting post styles.
n8n$14.99Telegram Bot with Supabase Memory and OpenAI Assistant Integration
### Video Guide I prepared a detailed guide that showed the whole process of building an AI bot, from the simplest version to the most complex in a template. [.png)](https://www.youtube.com/watch?v=QrZxuWgFqBI) ### Who is this for? This workflow is ideal for developers, chatbot enthusiasts, and businesses looking to build a dynamic Telegram bot with memory capabilities. The bot leverages OpenAI's assistant to interact with users and stores user data in Supabase for personalized conversations. ### What problem does this workflow solve? Many simple chatbots lack context awareness and user memory. This workflow solves that by integrating Supabase to keep track of user sessions (via `telegram_id` and `openai_thread_id`), allowing the bot to maintain continuity and context in conversations, leading to a more human-like and engaging experience. ### What this workflow does This Telegram bot template connects with OpenAI to answer user queries while storing and retrieving user information from a Supabase database. The memory component ensures that the bot can reference past interactions, making it suitable for use cases such as customer support, virtual assistants, or any application where context retention is crucial. 1. **Receive New Message:** The bot listens for incoming messages from users in Telegram. 2. **Check User in Database:** The workflow checks if the user is already in the Supabase database using the `telegram_id`. 3. **Create New User (if necessary):** If the user does not exist, a new record is created in Supabase with the telegram_id and a unique `openai_thread_id`. 4. **Start or Continue Conversation with OpenAI:** Based on the user's context, the bot either creates a new thread or continues an existing one using the stored `openai_thread_id`. 5. **Merge Data:** User-specific data and conversation context are merged. 6. **Send and Receive Messages:** The message is sent to OpenAI, and the response is received and processed. 7. **Reply to User:** The bot sends OpenAI's response back to the user in Telegram. ### Setup 1. **Create a Telegram Bot** using the [Botfather](https://t.me/botfather) and obtain the bot token. 2. **Set up Supabase:** 1. Create a new project and generate a `SUPABASE_URL` and `SUPABASE_KEY`. 2. Create a new table named `telegram_users` with the following SQL query: ``` create table public.telegram_users ( id uuid not null default gen_random_uuid(), date_created timestamp with time zone not null default (now() at time zone 'utc'), telegram_id bigint null, openai_thread_id text null, constraint telegram_users_pkey primary key (id) ) tablespace pg_default; ``` 3. **OpenAI Setup:** 1. Create an OpenAI assistant and obtain the `OPENAI_API_KEY`. 2. Customize your assistant's personality or use cases according to your requirements. 4. **Environment Configuration in n8n:** 1. Configure the Telegram, Supabase, and OpenAI nodes with the appropriate credentials. 2. Set up triggers for receiving messages and handling conversation logic. 3. Set up OpenAI assistant ID in **OPENAI - Run assistant** node.
n8n$14.99Automate Twitter Captions from Google Drive Images with Cloudinary and Azure OpenAI
This n8n workflow automates the creation of engaging Twitter captions by monitoring a Google Drive folder for new images, uploading them to Cloudinary, and using Azure OpenAI to generate optimized captions.
n8n$9.99OpenAI GPT-3: Company Enrichment from Website Content
Enrich your company lists with OpenAI GPT-3 You'll get valuable information such as: - Market (B2B or B2C) - Industry - Target Audience - Value Proposition This will help you to: - Add more personalization to your outreach - Make informed decisions about which accounts to target I've made the process easy with an n8n workflow. Here is what it does: - Retrieve website URLs from Google Sheets - Extract the content for each website - Analyze it with GPT-3 - Update Google Sheets with GPT-3 data
n8n$9.99Monitor Customer Churn Indicators with Bright Data MCP and OpenAI
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors customer churn indicators and early warning signals to help reduce customer attrition and improve retention rates. It saves you time by eliminating the need to manually track customer behavior and provides proactive insights for preventing customer churn. ## Overview This workflow automatically scrapes customer data sources, support tickets, usage analytics, and engagement metrics to identify patterns that indicate potential customer churn. It uses Bright Data to access customer data and AI to intelligently analyze behavior patterns and predict churn risk. ## Tools Used - **n8n**: The automation platform that orchestrates the workflow - **Bright Data**: For scraping customer data and analytics platforms without being blocked - **OpenAI**: AI agent for intelligent churn prediction and pattern analysis - **Google Sheets**: For storing churn indicators and customer retention data ## How to Install 1. **Import the Workflow**: Download the .json file and import it into your n8n instance. 2. **Configure Bright Data**: Add your Bright Data credentials to the MCP Client node. 3. **Set Up OpenAI**: Configure your OpenAI API credentials. 4. **Configure Google Sheets**: Connect your Google Sheets account and set up your churn monitoring spreadsheet. 5. **Customize**: Define customer data sources and churn indicator parameters. ## Use Cases - **Customer Success**: Proactively identify at-risk customers for retention efforts. - **Account Management**: Prioritize customer outreach based on churn probability. - **Product Teams**: Identify product issues that contribute to customer churn. - **Revenue Operations**: Reduce churn rates and improve customer lifetime value. ## 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 #churnprediction #customerretention #brightdata #webscraping #customeranalytics #n8nworkflow #workflow #nocode #churnindicators #customersuccess #retentionanalysis #customerchurn #customerinsights #churnprevention #retentionmarketing #customerdata #churnmonitoring #customerlifecycle #retentionmetrics #churnanalysis #customerbehavior #retentionoptimization #churnreduction #customerengagement #retentionstrategy #churnmanagement #customerhealth #retentiontracking
n8n$14.99Call Analyzer with AssemblyAI Transcription and OpenAI Assistant Integration
### Video Guide I prepared a detailed guide that showed the whole process of building a call analyzer. [.png)](https://www.youtube.com/watch?v=kS41gut8l0g) ### Who is this for? This workflow is ideal for sales teams, customer support managers, and online education services that conduct follow-up calls with clients. It's designed for those who want to leverage AI to gain deeper insights into client needs and upsell opportunities from recorded calls. ### What problem does this workflow solve? Many follow-up sales calls lack structured analysis, making it challenging to identify client needs, gauge interest levels, or uncover upsell opportunities. This workflow enables automated call transcription and AI-driven analysis to generate actionable insights, helping teams improve sales performance, refine client communication, and streamline upselling strategies. ### What this workflow does This workflow transcribes and analyzes sales calls using AssemblyAI, OpenAI, and Supabase to store structured data. The workflow processes recorded calls as follows: 1. **Transcribe Call with AssemblyAI**: Converts audio into text with speaker labels for clarity. 2. **Analyze Transcription with OpenAI**: Using a predefined JSON schema, OpenAI analyzes the transcription to extract metrics like client intent, interest score, upsell opportunities, and more. 3. **Store and Access Results in Supabase**: Stores both transcription and analysis data in a Supabase database for further use and display in interfaces. ### Setup #### Preparation 1. **Create Accounts**: Set up accounts for [N8N](https://n8n.partnerlinks.io/2hr10zpkki6a), [Supabase](https://supabase.com/), [AssemblyAI](https://www.assemblyai.com/), and [OpenAI](https://openai.com/). 2. **Get Call Link**: Upload audio files to public Supabase storage or Dropbox to generate a direct link for transcription. 3. **Prepare Artifacts for OpenAI**: - **Define Metrics**: Identify business metrics you want to track from call analysis, such as client needs, interest score, and upsell potential. - **Generate JSON Schema**: Use GPT to design a JSON schema for structuring OpenAI's responses, enabling efficient storage, analysis, and display. - **Create Analysis Prompt**: Write a detailed prompt for GPT to analyze calls based on your metrics and JSON schema. #### Scenario 1: Transcribe Call with AssemblyAI 1. **Set Up Request**: - **Header Authentication**: Set `Authorization` with AssemblyAI API key. - **URL**: POST to `https://api.assemblyai.com/v2/transcript/`. - **Parameters**: - `audio_url`: Direct URL of the audio file. - `webhook_url`: URL for an N8N webhook to receive the transcription result. - **Additional Settings**: - `speaker_labels` (true/false): Enables speaker diarization. - `speakers_expected`: Specify expected number of speakers. - `language_code`: Set language (default: `en_us`). #### Scenario 2: Process Transcription with OpenAI 1. **Webhook Configuration**: Set up a POST webhook to receive AssemblyAI's transcription data. 2. **Get Transcription**: - **Header Authentication**: Set `Authorization` with AssemblyAI API key. - **URL**: GET `https://api.assemblyai.com/v2/transcript/<transcript_id>`. 3. **Send to OpenAI**: - **URL**: POST to `https://api.openai.com/v1/chat/completions`. - **Header Authentication**: Set `Authorization` with OpenAI API key. - **Body Parameters**: - **Model**: Use `gpt-4-2024-08-06` for JSON Schema support, or `gpt-4-mini` for a less costly option. - **Messages**: - `system`: Contains the main analysis prompt. - `user`: Combined speakers' utterances to analyze in text format. - **Response Format**: - `type`: `json_schema`. - `json_schema`: JSON schema for structured responses. 4. **Save Results in Supabase**: - **Operation**: Create a new record. - **Table Name**: `demo_calls`. - **Fields**: - **Input**: Transcription text, audio URL, and transcription ID. - **Output**: Parsed JSON response from OpenAI's analysis.
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$24.99AI-Powered Speechwriting Coach via Telegram with OpenAI and Google Gemini
This n8n workflow serves as an AI speechwriting coach, accessible through Telegram. It provides feedback on speech drafts, refines content iteratively, and generates improved speeches using AI models from OpenAI and Google Gemini.
n8n$14.99Automate Company Data Enrichment from Google Sheets Using OpenAI and ScrapingBee
Enhance your company's data by automatically enriching it from Google Sheets using OpenAI's AI capabilities and ScrapingBee's web scraping technology.
n8n$9.99Automate Revenue Forecasting with Stripe, OpenAI, and Google Sheets
Leverage AI to transform Stripe sales data into actionable 3-month revenue forecasts, stored in Google Sheets and Supabase.
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$14.99Command-based Telegram Bot for Article Summarization & Image Prompts with OpenAI
# Telegram AI Assistant: Summarize Links & Generate Images On Demand This workflow turns any Telegram chat into a smart assistant. By typing simple commands like `/summary` or `/img`, users can trigger powerful AI actions directly from Telegram. --- ## What It Does This automation listens for specific commands in Telegram messages: - `/help`: Sends a help menu explaining available commands. - `/summary <link>`: Fetches a webpage, extracts its content, and summarizes it using OpenAI into 10-12 bullet points. - `/img <prompt>`: Sends the image prompt to OpenAI and replies that the request has been received (designed for future integration with image APIs). --- ## Features - Works instantly in Telegram - Uses OpenAI for text summarization and image prompt processing - Scrapes and cleans raw article text before summarizing - Replies directly to the same Telegram thread - Easily expandable to support more commands --- ## Use Cases - **Research Summaries**: Quickly condense articles or reports shared in chat. - **Content Review**: Get team-friendly TL;DRs of long blog posts or product pages. - **Creative Brainstorming**: Share visual ideas via `/img` and get quick prompts logged. - **Customer Support**: Offer instant answers in group chats (with further extension). - **Daily Digest Bot**: Connect to news feeds and auto-summarize updates. --- ## Getting Started 1. Clone this workflow and connect your Telegram Bot. 2. Insert your OpenAI credentials. 3. Deploy and test by messaging `/summary https://example.com` in your Telegram group or DM. 4. Expand with new commands or connect Stability.ai or other services for real image generation. --- ## Author & Resources Built by [Yaron Been](https://www.youtube.com/@YaronBeen/videos) Follow more automations at [nofluff.online](https://nofluff.online)
n8n$9.99Automate Project Kickoff with Dropbox, OpenAI, Slack & Gmail
Streamline project initiation by automatically creating structured folders in Dropbox and sending notifications via Slack and Gmail. This workflow enhances efficiency and collaboration by leveraging n8n's automation capabilities.
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$19.99Automate PDF to Vector Database Conversion with Google Drive, LangChain, and OpenAI
This workflow automates the extraction and vectorization of tour information from PDF files stored in Google Drive, utilizing OpenAI for embeddings and storing the results in a Pinecone vector database. Ideal for AI-powered search and recommendation systems.
n8n$9.99
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