AI Workflows
Artificial Intelligence tools and workflows
Context-Aware Document Processing from Google Drive to Pinecone
This n8n workflow automates the extraction, processing, and storage of document content from Google Drive into Pinecone using context-based chunking. It enhances retrieval accuracy for RAG setups by ensuring each chunk retains meaningful context.
n8n$14.99Automate Image Hosting and Optimization with ImgBB and ReSmush.it
Effortlessly convert and optimize images for web use by uploading them to ImgBB for URL generation and reducing their file size with ReSmush.it. Optionally, generate images using OpenAI.
n8n$9.99Generate Personalized Cold Outreach Icebreakers with GPT-4 and Google Sheets
## Automated Personalized Email Icebreakers This workflow automates creating personalized email icebreakers. It reads leads from a Google Sheet, scrapes their company website, uses OpenAI to analyze the data and craft a unique opening line, and then saves that icebreaker back into the original sheet. ## How It Works - **Fetch Lead**: The workflow starts, loops through your leads, and pulls one from your Google Sheet. - **Scrape & Summarize**: It scrapes the lead's company website and uses a fast OpenAI model to summarize the key points about the company and the person. - **Generate Icebreaker**: This summary is then sent to a more powerful OpenAI model, which follows specific instructions to write a short, personalized icebreaker. - **Update Sheet**: The new icebreaker is saved back into the correct lead's row in your Google Sheet, using their email to match the record. --- ## Requirements - An n8n instance. - An OpenAI API key with available credits. - A Google account with a Sheet for your leads. - The Google Sheet must have columns for lead data (e.g., `Email`, `Website`, `Company Name`) and an empty column named `icebreaker`. - The `Email` column must be unique for each lead. --- ## Setup Instructions 1. **Add Credentials**: In n8n, add your OpenAI API key and connect your Google account via the **Credentials** menu. 2. **Configure Google Sheets Nodes**: Select each of the two Google Sheets nodes (`Client data` and `Add icebreaker to sheet`). In each, choose your credential, select your spreadsheet and the specific sheet name, and ensure the column mapping is correct. 3. **Configure OpenAI Nodes**: Select both OpenAI nodes (`Summarizing prospect data` and `Creating icebreaker`) and choose your OpenAI credential from the dropdown. 4. **Verify Update Node**: On the final `Add icebreaker to sheet` node, ensure the **Operation** is set to `Append Or Update` and the **Matching Columns** field is set to `Email`. --- ## Customization Options - **Trigger**: Change the manual start to an automatic trigger, like when a new row is added to the sheet or on a daily schedule (Cron). - **AI Prompt**: Modify the prompt in the Creating icebreaker node to change the tone, style, or length of the output. - **AI Model**: Experiment with different OpenAI models (like `gpt-4`) for a different balance of cost, speed, and quality. - **Data Source**: Replace Google Sheets with a CRM like HubSpot or a database like Postgres.
n8n$9.99Automate LinkedIn Post Creation with OpenAI GPT-3
Leverage OpenAI GPT-3 to automatically generate and publish engaging LinkedIn posts, enhancing your social media strategy with AI-driven content.
MakeFreeAutomate Image Background Removal and Log Results in Google Sheets
Streamline your image processing workflow by automatically removing backgrounds using AI and logging the results in Google Sheets for easy tracking.
n8n$14.99Interact with Email History via Telegram Using Semantic and Structured Search
This workflow enables you to query your email history using both semantic and structured searches through Telegram. It leverages vector similarity searches and structured SQL queries to provide comprehensive answers from your email data.
n8n$14.99Integrate Telegram AI Bot with LangChain for Dynamic Conversations and Image Generation
This workflow connects a Telegram bot with LangChain nodes in n8n to create a dynamic AI-driven conversation agent. It utilizes OpenAI's GPT-4 for generating responses and Dall-E 3 for image creation upon user requests.
n8n$9.99AI-Powered Automated Job Search & Application
**Unleash the power of AI to automate your job search, tailor your applications, and boost your chances of landing your dream job!** This comprehensive workflow handles everything from finding relevant job postings to generating personalized resumes and cover letters. **Use cases are many:** * **Automate your entire job application process:** Spend less time searching and more time preparing for interviews. * **Tailor your resume and cover letter for every application:** Maximize your ATS compatibility and stand out to recruiters. * **Efficiently track your applications:** Keep all your job search activities organized in one place. * **Discover new job opportunities:** Leverage the Adzuna API to find relevant listings. --- **Good to know:** * **Free Adzuna API:** This workflow utilizes the free Adzuna API, making job search capabilities accessible without initial cost. * **OpenRouter Chat Model Costs:** AI model usage (for resume rewriting and cover letter generation) will incur costs based on the OpenRouter pricing model. Please check OpenRouter's official website for updated pricing information. * **Model Availability:** The AI models used may have geo-restrictions. If you encounter a model not found error, it might not be available in your country or region. --- **How it works:** 1. **Webhook Trigger:** The workflow is initiated via a webhook, allowing you to trigger it manually or integrate it with other systems (e.g., a form submission with your desired job title and resume). 2. **Resume Extraction:** Your uploaded resume (e.g., PDF) is automatically extracted into a readable text format. 3. **Job Search (Adzuna API):** Using the provided job title, the workflow queries the Adzuna API to fetch relevant job postings. 4. **Job Filtering:** Duplicate job listings are filtered out to ensure you receive unique opportunities. 5. **Job Info Extraction:** Key details like job description, company name, and job URL are extracted from each posting. 6. **Skills Extraction (AI):** An AI model (OpenRouter) analyzes the job description to identify the top skills and qualifications required. 7. **Resume Match Scoring (AI):** Your resume is compared against the extracted job skills by an AI model, generating a compatibility score (1-5). 8. **Conditional Resume & Cover Letter Generation:** If the resume match score is satisfactory (≥ 3): * **Tailored Resume Generation (AI):** An AI model rewrites your resume, specifically highlighting the skills and experience most relevant to the target job, in an ATS-friendly and human-readable JSON/HTML format. * **Personalized Cover Letter Generation (AI):** A custom cover letter is drafted by AI, uniquely tailored to the job description and your newly optimized resume, generated as well-formatted HTML. 9. **Google Sheets Integration:** The generated cover letter, tailored resume, job URL, and application status are automatically updated in your designated Google Sheet for easy tracking. 10. **Gmail Notification:** A personalized email containing the generated cover letter, tailored resume, and a direct link to the job posting on Adzuna is sent to your specified email address. 11. **Webhook Response:** A final text response is sent back via the webhook, summarizing the sent application materials. --- **How to use:** * **Manual Trigger:** The workflow is set up with a manual trigger (Webhook) for initial testing and demonstration. You can easily replace this with an n8n form, a scheduled trigger, or integrate it into your existing tools. * **Input:** Provide your desired job search keyword and your resume (e.g., as a PDF) to the webhook. * **Review & Apply:** Review the AI-generated cover letter and tailored resume sent to your email, then proceed to apply for the job using the provided Adzuna link. --- **Requirements:** * **n8n Instance:** A running n8n instance (self-hosted or cloud). * **Adzuna API Key:** A free Adzuna API key (easily obtainable from their developer portal). * **OpenRouter Account:** For AI model access (costs apply based on usage). * **Google Sheets Account:** To store and track your job applications. * **Gmail Account:** To send automated application emails. --- **Customizing this workflow:** This workflow is highly customizable. You can: * Integrate with other job boards (e.g., LinkedIn, Indeed) using their APIs. * Add more sophisticated AI models or custom prompts for even finer control over resume and cover letter generation. * Connect to other services for CRM, calendar management, or applicant tracking. * Implement different filtering criteria for job postings. * Expand the data stored in your Google Sheet (e.g., interview dates, feedback). Start automating your job search today and streamline your path to career success!
n8n$14.99Automated Document Q&A System with OpenAI, Pinecone, and Google Drive
This workflow automates the creation of a document-based Q&A system using OpenAI for embeddings, Pinecone for vector storage, and Google Drive for document retrieval. It supports natural language queries on stored documents.
n8n$14.99Automate Google AI Overview Extraction and SEO Analysis with n8n
Streamline the extraction of AI Overviews from Google Search and automate SEO recommendations using n8n. This workflow integrates with Google Sheets to store data and utilizes AI to generate actionable SEO guidelines.
n8n$14.99Automate Google Cloud Storage with AI-Generated Images Using n8n
Streamline your Google Cloud Storage management by integrating AI image generation with n8n. This workflow allows you to list, create, and manage storage buckets while generating and uploading AI-driven images.
n8n$14.99Automate Sentiment Analysis and Visualization of Google Sheets Reviews
Streamline your feedback process by automatically analyzing customer reviews from Google Sheets, categorizing sentiments, and visualizing the results with a chart sent via Gmail.
n8n$9.99Automate 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.
n8n$14.99Generate 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    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.
n8n$24.99Monitor and Summarize AI Token Usage for OpenAI and Gemini Models
This n8n workflow tracks and aggregates token usage metrics for AI models such as OpenAI and Gemini, providing a detailed breakdown of prompt, completion, and total tokens used.
n8n$9.99Voice-Activated AI Responses with Siri and Apple Shortcuts
Leverage Siri and Apple Shortcuts to trigger AI-driven responses using n8n. Customize inputs and outputs for a seamless voice-activated experience.
n8n$4.99Automate AI Image Creation and Storage with OpenAI and Azure Blob
This workflow automates the generation of AI images using OpenAI's DALL-E and stores them in Azure Blob Storage, providing a seamless no-code solution for managing cloud-based image storage.
n8n$14.99Transform 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.
n8n$9.99Automate Image Generation and Upload with Replicate and WordPress
This workflow generates images using Replicate's Flux models and uploads them to WordPress, with an optional upload to Twitter. It serves as a module for on-demand image creation, offering cost efficiency and flexibility.
n8n$9.99Voice Creation, SFX, Sound Effects, Voice Changer & More! Elevenlabs MCP Server
Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? [Join the community](https://www.skool.com/beyond-nodes-automation-lab-2006/about) This workflow provides a complete set of tools for interacting with the ElevenLabs voice API, enabling AI-powered text-to-speech, voice management, and audio processing capabilities. ## Features ### Text-to-Speech Operations - Convert text to speech with customizable voice settings - Generate speech with timestamps for precise audio control - Stream text-to-speech in real-time - Stream text-to-speech with timestamps for live applications ### Voice Management - List all available voices - Get detailed information about specific voices - Delete custom voices - Edit voice properties (name and description) - Find similar voices based on voice ID ### Audio Processing - Create transcripts from audio - Apply voice changing effects - Generate sound effects - Isolate audio components - Design and preview new voices - Save voice previews as new voices ## Requirements - An ElevenLabs API key - n8n instance with HTTP Request tool node - MCP Server Trigger node for AI integration ## Setup 1. Import the workflow into your n8n instance 2. Configure your ElevenLabs API key in the workflow settings 3. The workflow uses AI expressions for voice IDs with a fallback value of `Z9hrfEHGU3dykHntWvIY` ## Usage All nodes are connected to the MCP Server Trigger for AI-powered interactions ### Example Use Cases - Generate natural-sounding speech from text - Create and manage custom voices - Process and transform audio files - Build voice-based applications - Integrate ElevenLabs capabilities into existing workflows ## Technical Details - All endpoints use proper error handling - Voice ID parameters use AI expressions with fallback values - Nodes are organized in logical groups for better workflow management - Includes comprehensive parameter validation - Supports streaming and real-time processing ## Support For issues or questions, please refer to: - [ElevenLabs API Documentation](https://docs.elevenlabs.io) - [n8n Documentation](https://docs.n8n.io) - [n8n Community](https://community.n8n.io)
n8n$14.99Generate AI Media with ComfyUI: Images, Video, 3D, & Audio Bridge
Unlock low-cost, high-control generative media workflows directly from n8n by integrating with ComfyUI. Ideal for indie creators, AI developers, or small teams seeking scalable media automation—from images to video, 3D, and even audio—this workflow makes generative content production more flexible and programmable than ever. ## How it works - Accept a media generation request via an n8n trigger (HTTP webhook, schedule, etc.) - Parse input and inject it into a ComfyUI payload - Send the payload to your local or remote ComfyUI instance - Wait for and collect the output media files (e.g., images, videos, 3D models, or audio) - Send the result to a destination like email, Telegram, S3, or upload it back to a CMS or client app The format and complexity of the media are entirely dependent on the ComfyUI workflow you use, meaning this n8n integration is as powerful and creative as your ComfyUI setups. ## Set up steps 1. Set up and run a local or remote ComfyUI instance with API access enabled. 2. Load or create a ComfyUI workflow that suits your content goals (image gen, video stitching, etc.). 3. Open this n8n template and set your ComfyUI server URL, input template, and output handling preferences. 4. Connect additional services for input (e.g., Airtable, HTTP) and output (e.g., Notion, Slack, S3) depending on your use case.
n8n$24.99Automate UX Persona Creation with Data-Driven Insights
Streamline the creation of UX personas using market data and AI-generated insights, complete with visual representations and documentation.
n8n$14.99Adaptive RAG Strategy with Query Classification & Retrieval (Gemini & Qdrant)
This n8n workflow implements a version of the Adaptive Retrieval-Augmented Generation (RAG) framework. It recognizes that the best way to retrieve information often depends on the type of question asked. Instead of a one-size-fits-all approach, this workflow adapts its strategy based on the user's query intent. ## How it Works 1. **Receive Query:** Takes a user query as input (along with context like a chat session ID and Vector Store collection ID if used as a sub-workflow). 2. **Classify Query:** First, the workflow classifies the query into a predefined category. This template uses four examples: * **Factual:** For specific facts. * **Analytical:** For deeper explanations or comparisons. * **Opinion:** For subjective viewpoints. * **Contextual:** For questions relying on specific background. 3. **Select & Adapt Strategy:** Based on the classification, it selects a corresponding strategy to prepare for information retrieval. The example strategies aim to: * **Factual:** Refine the query for precision. * **Analytical:** Break the query into sub-questions for broad coverage. * **Opinion:** Identify different viewpoints to look for. * **Contextual:** Incorporate implied or user-specific context. 4. **Retrieve Info:** Uses the output of the selected strategy to search the specified knowledge base (Qdrant vector store - change as needed) for relevant documents. 5. **Generate Response:** Constructs a response using the retrieved documents, guided by a prompt tailored to the original query type. By adapting the retrieval strategy, this workflow aims to provide more relevant results tailored to the user's intent. ## Usage & Flexibility * **Sub-Workflow:** Designed to be called from other n8n workflows, passing `user_query`, `chat_memory_key`, and `vector_store_id` as inputs. * **Chat Testing:** Can also be triggered directly via the n8n Chat interface for easy testing and interaction. * **Customizable Framework:** The query categories (Factual, Analytical, etc.) and the associated retrieval strategies are examples. You can modify or replace them entirely to fit your specific domain or requirements. ## Requirements * **Credentials:** You will need API credentials configured in your n8n instance for: * Google Gemini (AI Models) * Qdrant (Vector Store)
n8n$24.99Transform 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.
n8n$14.99
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