by Cheng Siong Chin
How It Works A scheduled process aggregates content from eight distinct data sources and standardizes all inputs into a unified format. AI models perform sentiment scoring, detect conspiracy or misinformation signals, and generate trend analyses across domains. An MCDN routing model prioritizes and channels insights to the appropriate workflows. Dashboards visualize real-time analytics, trigger KPIs based on thresholds, and compile comprehensive market-intelligence reports for stakeholders. Setup Steps Data Sources: Connect news APIs, social media platforms, academic databases, code repositories, and documentation feeds. AI Analysis: Configure OpenAI models for sentiment analysis, conspiracy detection, and trend scoring. Dashboards: Integrate analytics platforms and enable automated email or reporting outputs. Storage: Configure a database for historical records, trend archives, and competitive-intelligence storage. Prerequisites Multi-source API credentials; OpenAI API key; dashboard platform access; email service; code repository access; academic database credentials Use Cases Competitive intelligence monitoring; market trend analysis; technology landscape tracking; product strategy research; misinformation filtering Customization Adjust sentiment thresholds; add/remove data sources; modify analysis rules; extend AI models Benefits Reduces research time 80%; consolidates market intelligence; improves decision accuracy
by MANISH KUMAR
This AI Blog Generator is an advanced n8n-powered automation workflow that leverages Google Gemini and Google Sheets to generate SEO-friendly blog articles for Shopify products. It automates the entire process — from fetching product data to creating structured HTML content — with zero manual effort. 💡 Key Advantages Our AI Blog Generator offers five core advantages that make it the perfect solution for automated content creation: 🔗 Shopify Product Sync** — Automatically pulls product data (titles, descriptions, images, etc.) via Shopify API. ✍️ SEO Blog Generation** — Gemini generates blog titles, meta descriptions, and complete articles using product information. 🗂️ Structured Content Output** — Creates well-formatted HTML with headers and bullet points for seamless Shopify blog integration. 📄 Google Sheets Integration** — Tracks blog creation and prevents duplicate publishing using a centralized Google Sheet. 📤 Shopify Blog API Integration** — Publishes the generated blog to Shopify with a single API call. ⚙️ How It Works The workflow follows a systematic 8-step process that ensures quality and efficiency: Step-by-Step Process Manual Trigger – Start the workflow via a test trigger or scheduler. Fetch Products from Shopify – Retrieves all product details, including images and descriptions. Fix Input Format – Organizes and updates the input table using Code and Google Sheet nodes. Filter Duplicates – Ensures no previously used rows are processed again. Limit Control – Processes one row at a time and loops until all blogs are posted. Gemini AI Generation – Creates SEO-friendly blog content in HTML format from product data. HTML Structure Fix – Adjusts content for JSON compatibility by cleaning unsupported HTML tags. Article API Posting – Sends finalized blog content to Shopify for publishing or drafting. 🛠️ Setup Steps Required Node Configuration To implement this workflow, you'll need to configure the following n8n nodes: Trigger Node:** Start the workflow instantly. Shopify Node:** Fetch product details. Google Sheet Node:** Store input/output data and track blog creation status. Code Node:** Format data as required. Filter Node:** Remove used rows to avoid duplication. Limit Node:** Process one blog at a time. Agent Node:** Sends prompt to Gemini and returns parsed SEO-ready content. HTTP Node:** Posts content to Shopify via the API. 🔐 Credentials Required Authentication Setup Before running the workflow, ensure you have the following credentials configured: Shopify Access Token** – For fetching products and posting blogs Gemini API Key** – For AI-powered blog generation Google Sheets OAuth** – For logging and tracking workflow data 👤 Ideal For Target Users This automation workflow is specifically designed for: Ecommerce teams** automating blogs for hundreds of products Shopify store owners** boosting organic traffic effortlessly Marketing teams** building scalable, AI-driven content workflows 💬 Bonus Tip Extensibility Features The workflow is fully modular and highly customizable. You can easily extend it for: Internal linking** between related products Multi-language translation** for global markets Social media sharing** automation Email marketing** integration All extensions can be implemented within the same n8n flow, making it a comprehensive content automation solution.
by Cheng Siong Chin
How It Works This workflow streamlines academic paper development through a multi-agent AI architecture that collects references, drafts individual sections autonomously, compiles the manuscript, and exports a professionally formatted DOCX file. Tailored for researchers, faculty members, and postgraduate students, it reduces the effort required to plan, write, and format scholarly articles from the ground up. Upon receiving a paper title and abstract, the system initiates web-based literature retrieval and reference extraction, handled by a Research Agent leveraging tools such as Google Scholar. A central Orchestration Agent then coordinates six dedicated writing agents, covering the Introduction, Related Work, Methodology, Results, Discussion, and Conclusion. The generated sections are consolidated with an automatically formatted bibliography, converted into a DOCX document via a document automation script, and prepared for download. Setup Steps Configure Research Paper Input node with topic, keywords, and paper parameters. Add Anthropic (Claude) API credentials to all Claude Model nodes. Set up Google Scholar Search Tool credentials or API key for literature retrieval. Connect Google Docs Script node with service account for DOCX generation. Configure workflow output path for DOCX file download or Drive storage. Prerequisites Google Scholar API or search tool access Google Docs Script or DOCX generation service Use Cases Automated first-draft generation for academic journal submissions Customization Swap Claude for OpenAI GPT-4 or NVIDIA NIM across writing agents Benefits Generates complete, structured research papers fully automatically
by Cheng Siong Chin
How It Works This workflow streamlines academic assessment through a multi-agent AI system that interprets rubrics, grades submissions, checks for plagiarism, performs quality moderation, generates feedback, and escalates borderline cases. Designed for educators and assessment administrators, it reduces inconsistencies in manual marking while embedding integrity checks into every evaluation cycle. A manual trigger retrieves student answers and rubrics, which are first structured before being sent to a Primary Marker Agent. If integrity concerns arise, a Plagiarism Analysis Agent runs in parallel. Results are consolidated and reviewed by a Quality Moderator Agent, followed by a Feedback Generator. Borderline cases are routed to a Secondary Marker Agent, while approved outcomes proceed to escalation preparation, Slack notifications, statistics computation, final consolidation, and logging in Google Sheets. Setup Steps Configure manual trigger and connect student answer and rubric data sources. Add OpenAI API credentials to all OpenAI Chat Model nodes. Define moderation thresholds in the Route by Moderation Decision rules node. Configure Slack credentials and set escalation alert channel. Set plagiarism sensitivity thresholds in the Plagiarism Analyser Agent node. Prerequisites Google Sheets with service account credentials Student answer and rubric data source (API or spreadsheet) Use Cases Automated essay and short-answer marking for university assessments Customization Replace OpenAI with Anthropic Claude for marking and moderation agents Benefits Automates end-to-end marking with built-in plagiarism and moderation checks
by NODA shuichi
Description: Automate your grant research with an AI Agent that reads, analyzes, and scores opportunities. 🏛️🤖 This advanced workflow transforms the tedious task of finding business subsidies into an automated intelligence stream. Unlike simple keyword scrapers, it uses an OpenAI Agent (GPT-4o) to read full articles, extract key details (deadlines, budgets), and evaluate their importance for SMEs on a 1-10 scale. Key Features: Intelligent Scoring: The AI assigns an "Importance Score" and "Urgency" level to each subsidy, filtering out noise. Structured Data Extraction: Converts unstructured news text into clean JSON (Deadlines, Requirements, Agencies). Smart Alerts: High-scoring subsidies (Score 7+) trigger a priority alert (🚨) sent directly to Chatwork. State Management: Uses Google Sheets to track history and prevent duplicate notifications. Organized Layout: Nodes are clearly grouped into sections (Setup, Aggregation, Analysis, Logic) for easy customization. How it works: Aggregate: Collects the latest articles from Google News, J-Net21, and Mirasapo Plus RSS feeds. Analyze: The AI Agent reads the content to extract fields like applicationDeadline and targetRecipients, while calculating an importance score. Deduplicate: Checks the URL against a Google Sheet database to ensure only new information is processed. Filter & Tag: High-value items are automatically tagged as "High Priority". Notify: Saves data to Google Sheets and sends a formatted message to Chatwork. Setup Requirements: Google Sheets: Create a sheet named Subsidies with the following headers in the first row: subsidyName, targetRecipients, applicationDeadline, budgetAmount, urgency, importanceScore, priorityTag, sourceUrl Credentials: OpenAI: API Key (GPT-4o recommended). Chatwork: API Token. Google Sheets: OAuth2 connection. Configuration: Open the "Sticky Note Setup" section (first node) and enter your Chatwork Room ID, Chatwork API Token, and Google Spreadsheet ID.
by rana tamure
This n8n workflow automates the creation of high-quality, SEO-optimized blog posts using AI. It pulls keyword data from Google Sheets, conducts research via Perplexity AI, generates structured content (title, introduction, key takeaways, body, conclusion, and FAQs) with OpenAI and Anthropic models, assembles the post, performs final edits, converts to HTML, and publishes directly to WordPress. Ideal for content marketers, bloggers, or agencies looking to scale content production while maintaining relevance and engagement. Key Features Keyword-Driven Generation: Fetches primary keywords, search intent, and related terms from a Google Sheets spreadsheet to inform content strategy. AI Research & Structuring: Uses Perplexity for in-depth topic research and OpenAI/Anthropic for semantic analysis, outlines, and full content drafting. Modular Content Creation: Generates sections like introductions, key takeaways, outlines, body, conclusions, and FAQs with tailored prompts for tone, style, and SEO. Assembly & Editing: Combines sections into a cohesive Markdown post, adds internal/external links, and applies final refinements for readability and flow. Publishing Automation: Converts Markdown to styled HTML and posts drafts to WordPress. Customization Points: Easily adjust AI prompts, research depth, or output formats via Code and Set nodes. Requirements Credentials: OpenAI API (for GPT models), Perplexity API (for research), Google Sheets OAuth2 (for keyword input), WordPress API (for publishing). Setup: Configure your Google Sheets with columns like "keyword", "search intent", "related keyword", etc. Ensure the sheet is shared with your Google account. Dependencies: No additional packages needed; relies on n8n's built-in nodes for AI, HTTP, and data processing. How It Works Trigger & Input: Start manually or schedule; pulls keyword data from Google Sheets. Research Phase: Uses Perplexity to gather topic insights and citations from reputable sources. Content Generation: AI nodes create title, structure, intro, takeaways, outline, body, conclusion, and FAQs based on research and SEO guidelines. Assembly & Refinement: Merges sections, embeds links, edits for polish, and converts to HTML. Output: Publishes as a WordPress draft or outputs the final HTML for manual use. Benefits Time Savings: Automate 80-90% of content creation, reducing manual writing from hours to minutes. SEO Optimization: Incorporates primary/related keywords naturally, aligns with search intent, and includes semantic structures for better rankings. Scalability: Process multiple keywords in batches; perfect for content calendars or high-volume blogging. Quality Assurance: Built-in editing ensures engaging, error-free content with real-world examples and data-backed insights. Versatility: Adaptable for any niche (e.g., marketing, tech, finance) by tweaking prompts or sheets. Potential Customizations Add more AI models (e.g., via custom nodes) for varied tones. Integrate image generation or social sharing for full content pipelines. Filter sheets for specific topics or add notifications on completion.
by Yevhenii
How it works Triggers when a message is received on Telegram. Checks conditions and either sends a default message or processes the message for content generation. Uses an AI agent to generate rich content including images and text. Formats and sends generated text in multiple languages (English, Polish, Spanish) over Telegram. Saves generated image data and logs it into a Google Sheet. Sends back image content to Telegram as a photo message. Setup steps Configure Telegram credentials in the Telegram Trigger and other Telegram nodes. Set up OpenAI API access for content generation. Connect to Google Sheets with appropriate API credentials. Customization Language options for text messages can be extended by adding more language nodes. Part of the AI Content Master system This workflow works together with the Moderator workflow: 👉 AI Content Master — Content Moderator with Telegram and Social Media Posting: https://n8n.io/workflows/15361
by Jamot
How it works Your WhatsApp AI Assistant automatically handles customer inquiries by linking your Google Docs knowledge base to incoming WhatsApp messages. The system instantly processes customer questions, references your business documentation, and delivers AI-powered responses through OpenAI or Gemini - all without you lifting a finger. Works seamlessly in individual chats and WhatsApp groups where the assistant can respond on your behalf. Set up steps Time to complete: 15-30 minutes Step 1: Create your WhapAround account and connect your WhatsApp number (5 minutes) Step 2: Prepare your Google Doc with business information and add the document ID to the system (5 minutes) Step 3: Configure the WhatsApp webhook and map message fields (10 minutes) Step 4: Connect your OpenAI or Gemini API key (3 minutes) Step 5: Send a test message to verify everything works (2 minutes) Optional: Set up PostgreSQL database for conversation memory and configure custom branding/escalation rules (additional 15-20 minutes) Detailed technical configurations, webhook URLs, and API parameter settings are provided within each workflow step to guide you through the exact setup process.
by Divyanshu Gupta
Before adding a new npm package as a dependency, you should know if it's actively maintained, widely used, and safe to build on. This workflow does that analysis automatically. Enter any package name, and the agent uses Firecrawl to find the right npm and GitHub pages, pulls live stats from the GitHub and npm APIs, then runs an AI analysis to generate a risk score and a clear recommendation: Use, Consider, or Avoid. What problem is it solving? Adding an unmaintained or poorly-supported npm package can create long-term technical debt such as security vulnerabilities, broken updates, or abandoned dependencies, that are hard to replace later. But manually checking npm downloads, GitHub stars, open issues, last commit date, and license type across multiple pages takes time and is easy to skip. This workflow makes due diligence effortless. In seconds, you get a structured report with all the signals that matter, plus an AI-generated recommendation you can act on immediately. What this workflow does Triggers via a simple form — enter any npm package name Normalises the input for consistent processing Uses Firecrawl to dynamically discover the correct npm page and GitHub repository URL (avoiding hardcoded assumptions) Cleans and validates the discovered URLs — filters out noise, adds fallbacks if npm page isn't found Fetches real-time data via APIs: GitHub API: stars, open issues, license, last commit date npm API: weekly download count Computes health metrics: issue-to-star ratio, activity status (active vs stale), package validity Handles errors gracefully — returns a safe default and explanation if the package isn't found or APIs fail Runs an AI Analysis Engine with a structured output parser to generate: Risk score: Low / Medium / High Adoption and health insights Final recommendation: Use / Consider / Avoid Sends a Slack report with the full analysis Setup Connect Firecrawl credentials — used to discover npm and GitHub URLs Connect OpenAI credentials (or OpenRouter — both are wired in) — used for AI analysis and structured output Connect GitHub credentials — used for the GitHub API node to fetch repo stats Connect Slack credentials — set the channel where reports should be posted in the Slack nodes Run — open the form trigger URL, enter a package name, and the report will appear in Slack within seconds How to customize this workflow to your needs Change the output channel** — swap the Slack nodes for email, a Notion database entry, or a webhook to your internal tooling Switch AI providers** — the workflow includes both OpenAI and OpenRouter nodes; use whichever you have access to and disable the other Adjust the risk scoring logic** — modify the Compute Health Metrics node to change what thresholds define Low / Medium / High risk Add more data sources** — extend the data collection phase with additional APIs (e.g. Snyk for security advisories, Bundlephobia for bundle size) Batch mode** — wrap the form trigger in a schedule and feed it a list of packages from a spreadsheet to audit your entire dependency list at once Embed in CI** — trigger the workflow via webhook from your CI pipeline to automatically flag risky new dependencies before they're merged
by Cheng Siong Chin
How It Works This workflow automates monthly tax processing by ingesting expense receipts alongside revenue data, extracting structured deduction details using GPT-4, and accurately matching expenses to their corresponding revenue periods. It retrieves receipts with built-in type validation, parses deduction information through OpenAI structured output extraction, and consolidates revenue records into a unified dataset. The system then intelligently aligns expenses with revenue timelines, calculates eligible deductions, and generates well-formatted tax reports that are automatically sent to designated agents via Gmail. Designed for accountants, tax professionals, and finance teams, it enables automated expense categorization and optimized deduction calculations. Setup Steps Configure receipt storage source and OpenAI Chat Model API key. Connect Gmail for report delivery and set up tax agent email. Define expense categories, revenue periods, and deduction rules. Schedule monthly trigger and test extraction Prerequisites Expense receipt repository; OpenAI API key; Gmail account; revenue data source Use Cases Accountants automating receipt processing for multiple clients; Customization Adjust extraction prompts for industry-specific expenses, modify deduction rules Benefits Eliminates manual receipt review, reduces categorization errors
by Cheng Siong Chin
How It Works This workflow streamlines financial operations for accounting teams, finance departments, and tax professionals managing business expenses. It addresses the challenge of reconciling expenses with revenue data, accurately categorizing deductions, and ensuring tax compliance across complex transactions. The system triggers on schedule to fetch expense receipts and revenue data from financial systems simultaneously. An AI-powered receipt matching agent uses OpenAI models to intelligently pair receipts with corresponding revenue entries, handling variations in formatting, dates, and vendor names. A deduction categorization agent analyzes matched transactions using structured output parsing to classify expenses into appropriate tax categories based on IRS guidelines and business rules. The workflow calculates optimized tax deductions considering category limits and compliance requirements. A report generation agent compiles comprehensive tax packets with supporting documentation, which are finalized and automatically delivered to tax agents via email for review and filing. Setup Steps Configure financial system API credentials in "Fetch Expense Receipts" Set up OpenAI API key in all AI agent nodes for intelligent processing Define schedule frequency in "Schedule Trigger" based on accounting period requirements Customize deduction categories and rules in "Deduction Categorization Agent" Configure tax calculation parameters in "Calculate Tax Deductions" node per regulations Prerequisites Financial system API access with read permissions, OpenAI API access. Use Cases Monthly expense reconciliation, quarterly tax preparation, annual tax filing automation Customization Add approval workflows for high-value expenses, integrate additional financial systems Benefits Reduces tax preparation time by 70%, maximizes legitimate deductions through intelligent categorization
by Rodrigo
How it works This workflow creates a complete AI-powered restaurant ordering system through WhatsApp. It receives customer messages, processes multimedia content (text, voice, images, PDFs, location), uses GPT-4 to understand customer intent and manage conversations, handles the complete ordering flow from menu selection to payment verification, and sends formatted orders to restaurant staff. The system maintains conversation memory, verifies payment receipts using OCR, and provides automated responses in multiple languages. Who's it for Restaurant owners, food delivery services, and hospitality businesses looking to automate customer service and order management through WhatsApp without hiring additional staff. Requirements WhatsApp Business API account OpenAI API key (GPT-4/GPT-4o access recommended) Supabase account (for conversation memory and vector storage) Google Drive account (for menu images and QR codes) Google Maps API key (for location services) Gemini API key (for PDF processing) How to set up Configure credentials - Add your WhatsApp Business API, OpenAI, Supabase, Google Drive, and Gemini API credentials to n8n Update phone numbers - Replace [PHONE_NUMBER] placeholders with your actual restaurant and staff phone numbers Customize restaurant details - Replace [RESTAURANT_NAME], [RESTAURANT_OWNER_NAME], and [BANK_ACCOUNT_NUMBER] with your information Upload menu images - Add your menu images to Google Drive and update the file IDs Set up Supabase - Create tables for chat memory and upload your menu/restaurant information to the vector database Configure AI prompts - Update the restaurant information in the AI agent system messages Test the workflow - Send test messages to verify all integrations work How to customize the workflow Menu management**: Update Google Drive file IDs to display your current menu images Payment verification**: Modify the receipt analysis logic to match your bank's receipt format Order formatting**: Customize the order confirmation template sent to kitchen staff AI personality**: Adjust the restaurant agent's tone and responses in the system prompts Languages**: The AI supports multiple languages - customize welcome messages for your target market Business hours**: Add time-based logic to handle orders outside operating hours Delivery zones**: Integrate with your delivery area logic using the location processing features