AI Automation Workflows — Page 30 | Neura Market
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    Artificial Intelligence tools and workflows

    • Automated WhatsApp Nutrition Consultant with AI

      Transform WhatsApp into a 24/7 nutrition consultant using AI for meal analysis and personalized dietary advice.

      n8nFree

    • Automate LinkedIn Profile Summaries with GPT-4 and Google Sheets

      Effortlessly convert LinkedIn profile URLs into AI-generated summaries using GPT-4, streamlining insights for recruiters and sales teams.

      n8nFree

    • Generate Content Ideas from PDFs with InfraNodus GraphRAG and AI Gap Analysis

      This template can be used to **find the content gaps in PDF documents** using the **[InfraNodus knowledge graph](https://infranodus.com) / GraphRAG text representation** and then **generate ideas / questions / AI prompts** that bridge those gaps based on optimizing the knowledge graph's structure. Simply **upload several PDF files** (research papers, corporate or market reports, etc.) and **generate an idea in seconds**. The template is **useful for:** - Generating ideas / questions for research - Generating content ideas based on competitors' discourse - Finding blind spots in any discourse and generating ideas that address them - Avoiding the generic bias of LLM models and focusing on what's important in your particular context ## What are Content Gaps and Knowledge Graphs? Knowledge graphs represent any text as a network: the main concepts are the nodes, their co-occurrences are the connections between them. Based on this representation, we build a graph and apply network science metrics to rank the most important nodes (concepts) that serve as the crossroads of meaning and also the main topical clusters that they connect. Naturally, some of the clusters will be disconnected and will have gaps between them. These are the topics (groups of concepts) that exist in this context (the documents you uploaded) but that are not very well connected. Addressing those gaps can help you see which groups of concepts you could connect with your own ideas. This is exactly what [InfraNodus](https://infranodus.com) does: builds the structure, finds the gaps, then uses the built-in AI to generate research questions and ideas that bridge those gaps. ![InfraNodus knowledge graph](https://infranodus.com/images/front/infranodus-structural-gaps-ideas.jpg) ## How it works 1) Step 1: First, you **upload your PDF files** using an online web form, which you can run from n8n or even make publicly available. 2) Steps 2-4: The documents are processed using the Code and PDF to Text nodes to **extract plain text** from them. 3) Step 5: This text is then sent to the **InfraNodus GraphRAG** node that creates a knowledge graph, identifies **structural gaps** in this graph, and then uses built-in AI to generate **ideas** or research **questions / prompts** (if you use the InfraNodus question module instead). 4) Step 6: The ideas are then **shown to the user** in the same web form. Optionally, you can hook this template to your own workflow and send the idea / question generated to your own AI model / agent for further processing. If you'd like to sync this workflow to PDF files in a Google Drive folder, you can copy our [Google Drive PDF processing workflow](https://n8n.io/workflows/4486-upload-google-drive-files-to-an-infranodus-graph/) for n8n. ## How to use You need an [InfraNodus GraphRAG API account and key](https://infranodus.com/use-case/ai-knowledge-graphs) to use this workflow. - Create an InfraNodus account - Get the API key at [https://infranodus.com/api-access](https://infranodus.com/api-access) and create a Bearer authorization key. - Add this key into the InfraNodus GraphRAG HTTP node(s) you use in this workflow. - You do not need any OpenAI keys for this to work. Optionally, you can change the settings in Step 4 of this workflow and enforce it to always use the biggest gap it identifies. ## Requirements - An [InfraNodus](https://infranodus.com/use-case/ai-knowledge-graphs) account and API key Note: OpenAI key is not required. You will have direct access to the InfraNodus AI with the API key. ## Customizing this workflow You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas). You can also hook up automated social media content creation workflows at the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way). Check out our **n8n templates** for ideas at [https://n8n.io/creators/infranodus/](https://n8n.io/creators/infranodus/) Also check the **full tutorial** with a **conceptual explanation** at [https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow](https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow) Also check out the **video introduction to InfraNodus** to better understand how knowledge graphs and content gaps work: [![Video tutorial](https://img.youtube.com/vi/8SAYDf9P7yg/sddefault.jpg)](https://www.youtube.com/watch?v=8SAYDf9P7yg) For **support and help** with this workflow, please contact us at [https://support.noduslabs.com](https://support.noduslabs.com)

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  1. Call 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. [![OPENAI 8.png](https://cflobdhpqwnoisuctsoc.supabase.co/storage/v1/object/public/my_storage/OPENAI%20(8).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.

    n8nFree

  2. AWS Cost & Usage Report Management for AI Agents

    Complete MCP server exposing 4 AWS Cost and Usage Report Service API operations to AI agents. ## Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator? All 100% free? [Join the community](https://www.skool.com/n8n-nodes-automation-lab-1570/about) 1. **Import** this workflow into your n8n instance 2. **Credentials** Add AWS Cost and Usage Report Service credentials 3. **Activate** the workflow to start your MCP server 4. **Copy** the webhook URL from the MCP trigger node 5. **Connect** AI agents using the MCP URL ## How it Works This workflow converts the AWS Cost and Usage Report Service API into an MCP-compatible interface for AI agents. - **MCP Trigger**: Serves as your server endpoint for AI agent requests - **HTTP Request Nodes**: Handle API calls to http://cur.{region}.amazonaws.com - **AI Expressions**: Automatically populate parameters via `$fromAI()` placeholders - **Native Integration**: Returns responses directly to the AI agent ## Available Operations (4 total) ### #X-Amz-Target=AWSOrigamiServiceGatewayService.DeleteReportDefinition (1 endpoint) - **POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.DeleteReportDefinition**: Deletes the specified report. ### #X-Amz-Target=AWSOrigamiServiceGatewayService.DescribeReportDefinitions (1 endpoint) - **POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.DescribeReportDefinitions**: Lists the AWS Cost and Usage reports available to this account. ### #X-Amz-Target=AWSOrigamiServiceGatewayService.ModifyReportDefinition (1 endpoint) - **POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.ModifyReportDefinition**: Allows you to programmatically update your report preferences. ### #X-Amz-Target=AWSOrigamiServiceGatewayService.PutReportDefinition (1 endpoint) - **POST /#X-Amz-Target=AWSOrigamiServiceGatewayService.PutReportDefinition**: Creates a new report using the description that you provide. ## AI Integration **Parameter Handling**: AI agents automatically provide values for: - Path parameters and identifiers - Query parameters and filters - Request body data - Headers and authentication **Response Format**: Native AWS Cost and Usage Report Service API responses with full data structure **Error Handling**: Built-in n8n HTTP request error management ## Usage Examples Connect this MCP server to any AI agent or workflow: - **Claude Desktop**: Add MCP server URL to configuration - **Cursor**: Add MCP server SSE URL to configuration - **Custom AI Apps**: Use MCP URL as tool endpoint - **API Integration**: Direct HTTP calls to MCP endpoints ## Benefits - **Zero Setup**: No parameter mapping or configuration needed - **AI-Ready**: Built-in `$fromAI()` expressions for all parameters - **Production Ready**: Native n8n HTTP request handling and logging - **Extensible**: Easily modify or add custom logic > **[Free for community use](https://github.com/Cfomodz/community-use)!** Ready to deploy in under 2 minutes.

    n8nFree

  3. Ultimate Content Generator for WordPress

    ## **Overview** This workflow automates the end-to-end process of creating, optimizing, and publishing content on WordPress. It integrates AI-powered tools, Airtable, and WordPress plugins to generate high-quality, on-brand posts effortlessly. Perfect for content creators, marketers, and business owners looking to save time and scale their content strategy. --- ## **Features** ### **Content Creation:** - **AI-Powered Content:** Generates SEO-friendly blog posts with structured headings, relevant keywords, and meta descriptions. - **Custom Prompts:** Tailor the AI-generated content to match your brand's tone and voice. ### **SEO Optimization:** - **RankMath Plugin Integration:** Updates RankMath SEO with focus keywords and meta descriptions, ensuring your content is search-engine optimized. ### **Content Management:** - **Airtable Integration:** Organizes content ideas, drafts, and publishing schedules in one place. Easily scalable for teams or solo creators. ### **Visuals:** - **Branded Featured Images:** Automatically generates on-brand images for every post. ### **Publishing:** - **Effortless Formatting:** Adapts content to fit your WordPress theme and schedules it for publication. --- ## **Workflow Steps** 1. **Trigger:** Initiated manually or on a schedule. 2. **Content Management:** Retrieves and organizes ideas from Airtable. 3. **Content Generation:** Generates AI-driven blog content tailored to your audience. 4. **SEO Optimization:** Automatically updates RankMath with SEO details. 5. **Featured Image Creation:** Produces on-brand images for the post. 6. **Publishing:** Formats and schedules the post on WordPress. --- ## **Prerequisites** ### **API Keys:** - OpenAI - Airtable - WordPress REST API - RankMath SEO Plugin ### **Custom Code:** Add a small update to your WordPress theme's `functions.php` file to enable seamless automation. --- ## **Customization** - Replace Airtable with another content management system if preferred. - Adjust AI prompts to reflect different tones, styles, or industries. - Add integrations for additional plugins, analytics, or storage services. --- ## **Usage** 1. Import the workflow into your n8n instance. 2. Configure API credentials for WordPress, Airtable, OpenAI, and RankMath. 3. Update your `functions.php` file with the provided code snippet. 4. Customize prompts and Airtable structure for your content needs. 5. Trigger the workflow manually or set it on a schedule. --- ## **Notes** - Experiment with Airtable views or add filters for more granular control over your content pipeline. - Extend the workflow to include social media posting or analytics tracking. - For questions, refer to n8n documentation or reach out to the creator. --- ## **Tools Used** - Airtable - OpenAI GPT - WordPress REST API - RankMath SEO Plugin Feel free to adapt and extend this workflow to meet your specific needs!

    n8nFree

  4. Build Comprehensive Entity Profiles with GPT-4, Wikipedia & Vector DB for Content

    This n8n template demonstrates how to build an intelligent entity research system that automatically discovers, researches, and creates comprehensive profiles for business entities, concepts, and terms. Use cases are many: try automating glossary creation for technical documentation, building standardized definition databases for compliance teams, researching industry terminology for content creation, or developing training materials with consistent entity explanations! ## Good to know Each entity research typically costs $0.08-$0.34, depending on the complexity and sources required. The workflow includes smart duplicate detection to minimize unnecessary API calls. The workflow requires multiple AI services and a vector database, so setup time may be longer than simpler templates. Entity definitions are stored locally in your Qdrant database and can be reused across multiple projects. ## How it works The workflow checks your existing knowledge base first to avoid duplicate research on entities you've already processed. If the entity is new, an AI research agent intelligently combines your vector database, Wikipedia, and live web research to gather comprehensive information. The system creates structured entity profiles with definitions, categories, examples, common misconceptions, and related entities - perfect for business documentation. AI-powered validation ensures all entity profiles are complete, accurate, and suitable for business use before storage. Each researched entity gets stored in your Qdrant vector database, creating a growing knowledge base that improves research efficiency over time. The workflow includes multiple stages of duplicate prevention to avoid unnecessary processing and API costs. ## How to use The manual trigger node is used as an example, but feel free to replace this with other triggers such as form submissions, content management systems, or automated content pipelines. You can research multiple related entities in sequence, and the system will automatically identify connections and relationships between them. Provide topic and audience context to get tailored explanations suitable for your specific business needs. ## Requirements - OpenAI API account for GPT-4-mini (entity research and validation) - Qdrant vector database instance (local or cloud) - Ollama with nomic-embed-text model for embeddings - **Automate Web Research with GPT-4, Claude & Apify for Content Analysis and Insights** workflow (for live web research capabilities) - Anthropic API account for Claude Sonnet 4 (used by the web research workflow) - Apify account for web scraping (used by the web research workflow) ## Customizing this workflow Entity research automation can be adapted for many specialized domains. Try focusing on specific industries like legal terminology (targeting official legal sources), medical concepts (emphasizing clinical accuracy), or financial terms (prioritizing regulatory definitions). You can also customize the validation criteria to match your organization's specific quality standards.

    n8nFree

  5. AI-Driven Local Event Discovery Using Multi-Tool Search

    This n8n workflow leverages AI and multiple search tools to find local events based on user criteria such as event type, location, date, and interests. It integrates Brave Web Search, Brave Local Search, Google Gemini Search, and Jina AI for comprehensive event discovery and data extraction.

    n8nFree

  6. Enhance 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).

    n8nFree

  7. Integrate OpenRouter with n8n for Dynamic LLM Model Selection

    Enable dynamic selection and configuration of LLM models in n8n versions prior to 1.78 using OpenRouter. This workflow allows you to leverage various LLM models by configuring OpenAI nodes with OpenRouter-specific settings.

    n8nFree

  8. Automate AI Content Creation and Management with Google Drive and Sheets

    Streamline your content creation process by automating article generation with AI, organizing files in Google Drive, and tracking progress in Google Sheets. Ideal for marketers, bloggers, and businesses.

    n8nFree

  9. Automate Sales Meeting Briefs with AI, LinkedIn, and WhatsApp Delivery

    This n8n workflow automates the generation of sales meeting briefs by integrating Google Calendar, enriching attendee data, and using AI to summarize social media activity. The formatted summaries are delivered via email and WhatsApp, enhancing sales preparation.

    n8nFree

  10. Automate Online Tool Discovery and Evaluation with GPT-4o and SerpAPI

    Streamline the process of finding and evaluating online tools with this workflow that leverages GPT-4o and SerpAPI to deliver comprehensive reviews and comparisons in seconds.

    n8nFree

  11. Extract Pay Slip Data with LINE Chatbot and Geminio to Google Sheets

    ## Workflow Overview: Extracting text from an image using AI is worthwhile because it requires no code. It incorporates the Google Gemini 2.0 Flash model for important text extraction from images. If you code without AI, you have to use multiple conditions and may cause a lot of bugs, but with Google Gemini, you don't need any coding, and if the Pay Slip is different, Gemini will extract it automatically. ## Workflow Description: 1. The user uses the Line Messaging API to send a Pay Slip image or message to the chatbot. Create a Line Business ID from here: [Line Business](https://account.line.biz/login). 2. Classify the message as either an image or text. 3. If the message is a Pay Slip image, it will be processed using Gemini 2.0 Flash EXP and extract important information and respond in JSON format without coding by using the following prompt: Analyze the image and then return in JSON Response that has the only following values: **Status, From, To, Date, Amount**. ![slip.png](fileId:995) To get the Google AI Studio API Key, you can find it from the following link: [Google AI Studio API Key](https://aistudio.google.com/apikey). 4. Create Google Sheets which include the fields **(Status, From, To, Date, Amount)** that we have created related to the AI prompt [Google Sheets](http://docs.google.com/spreadsheets) as the following example: ![Google Sheets Example.png](fileId:996) 5. If the message is text, it will process using the Gemini 2.0 Flash EXP model as the AI Assistant; else if the message is an image, it will extract the important fields, then reply to the user and insert into Google Sheets. ## Key Features: * **Extract text from image with No Code** - Without N8N, we have to write code to extract text from an image, but with N8N and Google Gemini 2.0 Flash EXP together, we don't need to code, and it will process all slip vendors or other document vendors. * **Multipurpose Chatbot** - This chatbot accepts both text and image, so we don't have to create many chatbot accounts. * **Reduce human error** - This workflow lets any officer verify document status when the job ends. **Note:** You can change the information by changing your prompt and also Google Sheets Column names relatively.

    n8nFree

  12. Automate AI-Powered Document Retrieval with Paul Essays, Milvus, and OpenAI

    This workflow automates the creation of a document-based AI retrieval system using Milvus and OpenAI. It processes Paul Graham essays, stores them in a Milvus vector database, and generates cited responses to user queries.

    n8nFree

  13. Microsoft Outlook AI Email Assistant with Contact Support from Monday and Airtable

    # Microsoft Outlook AI Email Assistant ## **Prerequisites** ### **1. Microsoft 365 Login Credentials** - Provide your Office 365 credentials to connect to Outlook. ### **2. Monday.com** - Generate an API token and have a board with your contact details. ### **3. Airtable** - Obtain an API key (or personal access token) and set up a base to store: - **Contacts** (populated by the Monday.com sync). - **Rules & Categories** (used by the AI Email Assistant). - Use this Airtable base as the template: [Airtable AI Email Assistant Template](https://airtable.com/appuffxqy5HlNYAXJ/shrhb292ZMF8FezS/tblP9SIola8yglSc0/viwxAIMM6vWoahfM?blocks=hide). Define your own rules, categories, and delete rules. ### **4. OpenAI API Key** - Sign up for OpenAI if you don't already have an account. - Generate a new API key at [OpenAI API Keys](https://platform.openai.com/api-keys). --- ## **What the System Does** ### **1. Daily Contact Sync (Monday.com → Airtable)** - Runs **once a day** to pull the latest contacts from Monday.com and store or update them in Airtable. ### **2. AI Email Categorisation & Prioritisation** - Fetches **Outlook emails** with filters. - Cleans and processes email content. - Matches emails with known contacts from Airtable. - Uses an **AI agent** to classify, categorize, and prioritize emails. - Updates **Outlook categories and importance** based on AI results. - Runs in parallel with **Airtable rules & categories retrieval** for real-time decision-making. --- # **Workflow 1: Daily Contact Sync (Monday.com → Airtable)** ### **Purpose** Keep Airtable's **Contacts** table up to date by pulling new or updated contact data from Monday.com **daily**. ### **Steps** 1. **Schedule Trigger** - Runs at a set interval (daily) to initiate contact syncing. 2. **Monday.com: Get Contacts** - Reads the specified **board/columns** from Monday.com where you store contact details. 3. **Airtable - Contacts** - **Upserts** (adds or updates) the fetched Monday.com data into Airtable's **Contacts** table. - Ensures **daily updates** reflect changes from Monday.com. ### **Result** A **consolidated contact list** in Airtable, ready for AI email categorization. --- # **Workflow 2: Categorize & Prioritize Outlook Emails** ### **Purpose** Fetches **Outlook emails**, cleans and processes their content, **matches senders** with known contacts, and uses AI to categorize and prioritize them. ### **Steps** #### **1. Get Outlook Emails with Filters** - **Trigger**: Either scheduled (`Check Mail Schedule Trigger`) or manual (`Test Workflow`). - **Outlook Filters**: - **Not flagged** (`flag/flagStatus == notFlagged`). - **Not categorized** (`not categories/any()`). **→ Result**: A batch of **fresh, unprocessed emails** ready for processing. --- #### **2. Sanitize Email** - **Convert to Markdown**: Strips **HTML tags** and normalizes formatting. - **Email Messages Processing**: Allows manual removal of **signatures, disclaimers, or extra content**. **→ Result**: A **clean, AI-friendly email** for categorization. --- #### **3. Match Contact** - **Loop Over Emails**: Iterates over each email. - **Contact Lookup**: Checks Airtable's **Contacts** table (updated daily). - **Merge Data**: Enriches emails with known **client, supplier, or internal team** info. **→ Result**: Enhanced email context **for AI processing**. --- #### **4. AI Agent to Categorize & Prioritize** - **Retrieve Rules & Categories** - Reads **Rules, Categories, and Delete Rules** from Airtable in parallel. - **AI: Analyze Email (Tools Agent)** - Uses **email text, sender info, and rules** to build a **structured AI prompt**. - **OpenAI Chat Model** - Processes the AI prompt and outputs: - **Category** - **Subcategory (optional)** - **Priority level** - **Short rationale** - **Structured Output Parser** - Ensures AI response is in valid **JSON format**. **→ Result**: Each email is **labeled, categorized, and prioritized** with AI-driven logic. --- #### **5. Set Outlook Category & Importance** - **Set Category**: Updates Outlook with the assigned **category**. - **Check Priority Conditions** (`If` Node): - If **Action Required** or from a VIP, mark as **High Priority**. - **Set Importance**: Updates the email's **importance flag** in Outlook. **→ Result**: Outlook is updated with **categories & importance** based on AI recommendations. --- ## **Parallel Processing: Retrieve Rules & Categories** - Runs **alongside** the email categorization workflow. - Ensures **Airtable-based rules** are available before AI processing. ### **Steps** 1. **Airtable: Get Rules & Categories** - Fetches **Rules, Categories, and Delete Rules** from Airtable. 2. **Delete Rules (Optional)** - If a delete rule matches, the email is removed. **→ Result**: A dynamic, **updatable rule system** ensuring emails are handled properly. --- ## **Final Outcome** - **Daily Contact Sync** keeps the contact list consolidated and up to date for AI email categorization.

    n8nFree

  14. Automate Job Listings Extraction from Hacker News to Airtable with AI

    This workflow automates the extraction and structuring of job listings from Hacker News using AI, and saves them into Airtable for easy access and management.

    n8nFree

  15. Interactive AI Chatbot with Custom JavaScript Color Selector

    This workflow creates an AI-powered conversational agent that returns a random color, excluding specified colors, using custom JavaScript code. Ideal for dynamic user interactions and personalized responses.

    n8nFree

  16. Automate Loom Video Analysis with Gemini and Slack Notifications

    This workflow automates the process of downloading Loom videos, analyzing them with Google Gemini, and sending the results to Slack. It streamlines video content analysis and communication.

    n8nFree

  17. Interact with OpenAI's GPT-3.5 via a Telegram Bot

    Enable seamless communication with OpenAI's GPT-3.5 through a Telegram bot, providing AI-driven responses with emojis to user messages.

    n8nFree

  18. Automate AI-Powered Voice Note Processing and Email Delivery

    Streamline the conversion of voice notes into AI-driven responses, saving results in a database and delivering them via email.

    n8nFree

  19. Automated Video Translation & Distribution with DubLab to Multiple Platforms

    **Automated** n8n workflow: Receives videos via form, dubs/translates them to the selected languages, and—upon completion—uploads them to multiple social media channels and cloud drives, including Box, Dropbox, and YouTube, Telegram, Postiz (Facebook, Instagram, TikTok, Reddit, etc.) ### Workflows 1. Via n8n form, select files to dub for desired languages. 2. Listen to webhook and whenever dubbing finishes, upload to desired platforms. ### Used Stacks - DubLab App (ApiKey, Webhook Setup Required) #### Optional (Upload) - Telegram (Token Required) - Box (OAuth2 Required) - Dropbox (OAuth2 Required) - YouTube (OAuth2 Required) - Postiz (ApiKey Required)

    n8nFree

  20. Automate LinkedIn Content Creation from Meeting Transcripts with AI and Google Docs

    Effortlessly convert your meeting transcripts into engaging LinkedIn posts using AI, Google Docs, and Gmail. Ideal for professionals looking to streamline content creation.

    n8nFree

  21. Automate AI Image Generation with IBM Granite Vision 3.3 2B via Replicate

    Streamline your image generation process by integrating IBM Granite Vision 3.3 2B with Replicate API in n8n. This workflow automates API authentication, parameter setup, and image creation, enhancing efficiency and reliability.

    n8nFree
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