Workflow Templates

This n8n template creates an intelligent expense tracking system 🤖 that processes text, voice, and receipt images through Telegram. The assistant automatically categorizes expenses, handles currency conversions 🌍, and maintains financial records in Google Sheets while providing smart spending insights 💡. Use Cases: 🗣️ Personal expense tracking via Telegram chat 🧾 Receipt scanning and data extraction 💱 Multi-currency expense management 📂 Automated financial categorization 🎙️ Voice-to-expense logging 📊 Daily/weekly/monthly spending analysis How it works: Multi-Input Processing: Telegram trigger captures text messages, voice notes, and receipt images. Content Analysis: A Switch node routes different input types (text, audio, images) to appropriate processors. Voice Processing: ElevenLabs converts voice messages to text for expense extraction. Receipt OCR: Google Gemini analyzes receipt images to extract amounts and descriptions. Expense Classification: An LLM determines if the input is an expense or a general query. Expense Parsing: For multiple expenses, the AI splits and normalizes each item. Currency Conversion: An exchange rate API converts foreign currencies to USD. Smart Categorization: The AI agent assigns expenses to predefined categories with emojis. Data Storage: Google Sheets stores all expense records with automatic totals. Intelligent Responses: The agent provides spending summaries, alerts, and financial insights. Requirements: 🌐 Telegram Bot API access 🤖 OpenAI, Gemini, or any other AI model 🗣️ ElevenLabs API for voice processing 📝 Google Sheets API access 💹 Exchange rate API access Good to know: ⚠️ Daily spending alerts trigger when expenses exceed 100 USD. 🏷️ Supports 12 predefined expense categories with emoji indicators. 🔄 Automatic currency detection and conversion to USD. 🎤 Voice messages are processed through speech-to-text. 📸 Receipt images are analyzed using computer vision. Customizing this workflow: ✏️ Modify expense categories in the system prompt. 📈 Adjust spending alert thresholds. 💵 Change the base currency from USD to your preferred currency. ✅ Add additional expense validation rules. 🔗 Integrate with other financial platforms.

AI-Powered Email Generation with MadKudu sent via Outreach.io This workflow researches prospects using MadKudu MCP, generates personalized emails with OpenAI, and syncs them to Outreach with automatic sequence enrollment. Its for SDRs and sales teams who want to scale personalized outreach by automating research and email generation while maintaining quality. ✨ Who it's for Sales Development Representatives (SDRs) doing cold outreach Business Development teams needing personalized emails at scale RevOps teams wanting to automate prospect research workflows Sales teams using Outreach for email sequences 🔧 How it works 1. Input Email & Research: Enter prospect email via chat trigger. Extract email and generate comprehensive account brief using MadKudu MCP account-brief-instructions. 2. Deep Research & Email Generation: AI Agent performs 6 research steps using MadKudu MCP tools: Account details (hiring, partnerships, tech stack, sales motion, risk) Top users in the account (for name-dropping opportunities) Contact details (role, persona, engagement) Contact web search (personal interests, activities) Contact picture web search (LinkedIn profile insights) Company value prop research AI generates 5 different email angles and selects the best one based on relevance. 3. Outreach Integration: Checks if prospect exists in Outreach by email. If exists: Updates custom field (custom49) with generated email. If new: Creates new prospect with email in custom field. Enrolls prospect in specified email sequence (ID 781) using mailbox (ID 51). Waits 30 seconds and verifies successful enrollment. 📋 How to set up Set your OpenAI credentials Required for AI research and email generation. Create a n8n Variable to store your MadKudu API key named madkudu_api_key Used for the MadKudu MCP tool to access account research capabilities. Create a n8n Variable to store your company domain named my_company_domain Used for context in email generation and value prop research. Create an Oauth2 API credential to connect your Outreach account Used to create/update prospects and enroll in sequences. Configure Outreach settings Update Outreach Mailbox ID (currently set to 51) in the "Configure Outreach Settings" node. Update Outreach Sequence ID (currently set to 781) in the same node. Adjust custom field name if using different field than custom49. 🔑 How to connect Outreach In n8n, add a new Oauth2 API credential and copy the callback URL Now go to Outreach developer portal Click "Add" to create a new app In Feature selection add Outreach API (OAuth) In API Access (Oauth) set the redirect URI to the n8n callback Select the following scopes accounts.read, accounts.write, prospects.read, prospects.write, sequences.read Save in Outreach 7.Now enter the Outreach Application ID into n8n Client Id and the Outreach Application Secret into n8n Client secret Save in n8n and connect via Oauth your Outreach Account ✅ Requirements MadKudu account with access to API Key Outreach Admin permissions to create an app OpenAI API Key 🛠 How to customize the workflow Change the research steps Modify the AI Agent prompt to adjust the 6 research steps or add additional MadKudu MCP tools. Update Outreach configuration Change Mailbox ID (51) and Sequence ID (781) in the "Configure Outreach Settings" node. Update custom field mapping if using different field than custom49. Modify email generation Adjust the prompt guidelines, tone, or angle priorities in the "AI Email Generator" node. Change the trigger Swap the chat trigger for a Schedule, Webhook, or integrate with your CRM to automate prospect input.

Try It Out! Use n8n to extract medical test data from diagnostic reports uploaded to Google Drive, automatically detect abnormal values, and generate personalized health advice. How it works Upload a medical report (PDF or image) to a monitored Google Drive folder Mistral AI extracts text using OCR while preserving document structure GPT-4 parses the extracted text into structured JSON (patient info, test names, results, units, reference ranges) All test results are saved to the "All Values" sheet in Google Sheets JavaScript code compares each result against its reference range to detect abnormalities For out-of-range values, GPT-4 generates personalized dietary, lifestyle, and exercise advice based on patient age and gender Abnormal results with recommendations are saved to the "Out of Range Values" sheet How to use Set up Google Drive folder monitoring and Google Sheets with two tabs: "All Values" and "Out of Range Values" Configure API credentials for Google Drive, Mistral AI, and OpenAI (GPT-4) Upload medical reports to your monitored folder Review extracted data and personalized health advice in Google Sheets Requirements Google Drive and Sheets with OAuth2 authentication Mistral AI API key for OCR OpenAI API key (GPT-4 access required) for intelligent extraction and advice generation Need Help? See the detailed Read Me file at https://drive.google.com/file/d/1Wv7dfcBLsHZlPcy1QWPYk6XSyrS3H534/view?usp=sharing Join the n8n community forum for support

🧠 Export Tawk.to Help Center Articles to Google Drive as Markdown Files Transform the way you manage your knowledge base with this fully automated N8N workflow! This automation connects directly to your Tawk.to Help Center, reads all published categories and articles, converts them to Markdown (.md) format, and uploads each file to Google Drive 🔹 Key Benefits 🚀 Complete Extraction Automatically captures all categories and articles from your Tawk.to Help Center, even without direct API integration. 🧩 Automatic Conversion Transforms HTML content into clean Markdown files — perfect for editing, version control, or migration to another CMS. ☁️ Native Google Drive Integration Saves each article with a structured filename, avoids duplicates, and organizes them by category. 🔁 Fully Customizable Easily adapt the workflow to export to Notion, GitHub, Dropbox, or any other platform supported by N8N. 💡 Ideal Use Cases Migrating your Tawk.to Help Center Creating automated content backups Integrating documentation across multiple systems ⚙️ Prerequisites Before running this workflow, make sure you have: An active Tawk.to account with access to your Help Center. A Google Drive account (personal or workspace). Access to N8N (self-hosted or cloud). 🧰 Setup Instructions Import the Workflow Download the JSON file from the provided link or your N8N community instance. In N8N, click Import Workflow and upload the file. Authenticate Google Drive Open the Google Drive node. Click Connect, choose your Google account, and allow access. Configure Output Folder Choose or create a target folder in your Google Drive where articles will be saved. Run the Workflow Click Execute Workflow. The automation will read all Help Center articles, convert them to Markdown, and save them to your Drive.

This AI-powered workflow transforms n8n workflow JSON files into publication-ready, SEO-optimized markdown posts for the n8n community. Simply upload your workflow's JSON, and let Google Gemini 2.5 Pro, guided by a LlamaIndex-powered knowledge base of best practices, automatically generate compelling content. Why Use This Workflow? Time Savings: Reduces the time to create a detailed workflow post from over an hour of manual writing to under 2 minutes. Cost Reduction: Eliminates the need for separate AI content subscriptions or outsourcing content creation tasks. Error Prevention: Enforces content quality and structural consistency by using a knowledge base of n8n's official guidelines, minimizing formatting errors. Ideal For n8n Workflow Creators:** To quickly document and share their creations on the community platform without the tedious, time-consuming writing process. Developer Advocates:** To standardize and accelerate the production of technical tutorials and workflow showcases. Content & Marketing Teams:** To streamline the content pipeline for n8n-related blog posts, tutorials, and community engagement initiatives. How It Works Trigger: The process starts when you upload an n8n workflow JSON file via a simple web form. Data Extraction: The workflow automatically extracts the JSON content from the uploaded file. Intelligence Layer: An advanced AI agent, powered by Google Gemini 2.5 Pro, analyzes the structure, nodes, and metadata of your workflow. Knowledge Retrieval: The agent consults a specialized, in-memory knowledge base built from n8n's content guidelines. This knowledge base is created by parsing documents with LlamaIndex and refined with a Cohere Reranker for maximum accuracy. Content Generation: The AI agent synthesizes the technical details from your JSON with the best practices from the knowledge base to write a complete, benefit-driven markdown post. Output & Delivery: The final, polished markdown content is generated as the workflow's output, ready to be copied and pasted into the n8n community platform. Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Workflow execution platform | | Google Gemini API Key | Essential | Powers the core AI content generation | | LlamaIndex Cloud API Key | Essential | Parses documents for the knowledge base | | Cohere API Key | Optional | Improves knowledge base search results | | Google Drive Account | Optional | For automatically updating the knowledge base from a Google Doc | Installation Steps Import the JSON file to your n8n instance. Configure credentials: Google Gemini: In the "GEmini 2.5 pro" node, create and add your Google Gemini API credential. LlamaIndex: In the three HTTP Request nodes named "Parse Document...", "Monitor Document...", and "Retrieve Parsed...", create an HTTP Header Auth credential. The header name is Authorization and the value is Bearer YOUR_LLAMA_INDEX_API_KEY. Cohere: (Optional) In the "Reranker Cohere" node, create and add your Cohere API credential. Google Drive: (Optional) If you plan to auto-update the knowledge base, configure Google Drive OAuth2 credentials for the "Knowledge Base Updated Trigger" and "Download Knowledge Document" nodes. Update environment-specific values: To use the knowledge base auto-update feature, go to the "Knowledge Base Updated Trigger" node and select the Google Drive file containing your content guidelines. Customize settings: The primary system prompt in the "n8ncreator" agent node can be modified to adjust the tone, style, or structure of the generated content. Test execution: Run the workflow manually and use the form to upload a sample n8n workflow JSON file to verify that all connections work correctly. Technical Details Core Nodes | Node | Purpose | Key Configuration | |------|---------|-------------------| | Form Trigger | Initiates the workflow via a file upload. | Set the "Input Json Workflow" field to required. | | Langchain Agent | Orchestrates the entire content creation process. | The system prompt contains all instructions for the AI. | | ChatGoogleGemini | Provides the core generative AI capabilities. | Select your Gemini model of choice (e.g., gemini-2.5-pro). | | VectorStoreInMemory | Acts as the agent's knowledge base tool. | Configured to use embeddings from a Google Gemini model. | | HTTPRequest | Interacts with the LlamaIndex API to parse documents. | Set up with LlamaIndex API endpoint and authentication. | Customization Options Basic Adjustments: Change AI Model:** Replace the ChatGoogleGemini node with another LLM node (e.g., OpenAI, Anthropic) to use a different provider. Adjust System Prompt:** Modify the prompt in the "n8ncreator" node to tailor the output for different platforms (e.g., blog, internal wiki) or change the writing style. Advanced Enhancements: Automated Publishing:** Connect the output of the "n8ncreator" node to a Ghost, WordPress, or GitHub node to automatically publish the generated post. Add Web Search:** Equip the Langchain Agent with a web search tool to allow it to fetch live information about new n8n nodes or services. Batch Processing:** Replace the Form Trigger with a Read Binary Files node to process an entire folder of workflow JSON files in a single run. Performance & Optimization | Metric | Expected Performance | Optimization Tips | |--------|---------------------|-------------------| | Execution time | ~1 minute per run | Largely dependent on the Gemini API response time. | | API calls | 1 LLM call per post | Knowledge base updates trigger LlamaIndex/Google calls separately. | | Error handling | Built-in retry logic for document parsing | Add an error workflow path after the "n8ncreator" node to handle AI generation failures. | Troubleshooting Common Issues: | Problem | Cause | Solution | |---------|-------|----------| | AI output is generic or incomplete | The input JSON file is invalid or lacks key information (e.g., no node names). | Ensure you are uploading a valid, exported n8n workflow JSON. Verify the workflow has been saved with descriptive node names. | | LlamaIndex parsing fails | The LlamaIndex API key is incorrect or the source document is inaccessible. | Double-check your LlamaIndex API credential. Ensure the Google Doc sharing settings allow access. | | Credential Error | API keys are missing or incorrect for Gemini, LlamaIndex, or Cohere. | Go to the specified nodes and verify that the correct credentials have been created and selected. | Created by: khaisa Studio Category: AI Tags: AI, Content Generation, Google Gemini, LlamaIndex, Automation Need custom workflows? Contact us Connect with the creator: Portfolio • Workflows • LinkedIn • Medium • Threads

Automated workflow that generates custom AI image backgrounds from text prompts using Gemini's Nano Banana (native image generation), removes video backgrounds, and composites videos on AI-generated scenes. Create any background you can imagine without needing stock images. How it works • Describe background: Provide video URL and text prompt describing desired background scene (e.g., "modern office with city skyline at golden hour") • AI generates image: Gemini creates a background image from your prompt in ~10-20 seconds • Upload to Drive: Generated background is saved to Google Drive and made publicly accessible • Remove & composite: Video background is removed and composited on AI-generated scene with centered template • Save final video: Completed video is uploaded to Google Drive with shareable link Set up steps ⏱️ Total setup time: ~5 minutes • Get Gemini API Key (~1 min): Visit https://aistudio.google.com/apikey, create new API key, add to n8n Settings → Variables as GEMINI_KEY • Get VideoBGRemover API Key (~2 min): Visit https://videobgremover.com/n8n, sign up, add to n8n as VIDEOBGREMOVER_KEY • Connect Google Drive (~2 min): Click "Save Background Image to Drive" node, click "Connect", authorize n8n Use cases: Marketing videos with custom branded environments tailored to your message Product demos with unique AI-generated backgrounds that match your product aesthetic Social media content with creative scenes you can't find in stock libraries AI avatars placed in AI-generated worlds Presentations with custom backgrounds generated for specific topics A/B testing different background variations for the same video Pricing: Gemini: ~$0.03 per generated image VideoBGRemover: $0.50-$2.00 per minute of video Total: ~$0.53-$2.03 per video Triggers: Webhook (for automation) or Manual (for testing) Processing time: Typically 5-7 minutes total Prompt tips: Be descriptive and specific. Instead of "office," try: "A modern minimalist office with floor-to-ceiling windows overlooking a city skyline at golden hour. Warm sunlight, polished concrete floors, sleek wooden desks, green plants."

Auto-Call Leads from Google Sheets with VAPI → Log Results + Book Calendar This workflow calls new leads from a Google Sheet using VAPI, saves the call results, and (if there’s a booking request) creates a Google Calendar event automatically. Benefits Auto-call each new lead from your call list Save full call outcomes back to Google Sheets Parse “today/tomorrow + time” into a real datetime (IST) Auto-create calendar events for bookings/deliveries Batch-friendly to avoid rate limits How It Works Trigger: New row in Google Sheets (call_list). Prepare: Normalize phone (adds +), then process in batches. Call: Send number to VAPI (/call) with your assistantId + phoneNumberId. Receive: VAPI posts results to your Webhook. Store: Append/Update Google Sheet with: name, role, company, phone, email, interest level, objections, next step, notes, etc. Parse Time: Convert today/tomorrow + HH:MM AM/PM to start/end in IST (+1 hour). Book: Create Google Calendar event with the parsed times. Respond: Send response back to VAPI to complete the cycle. Who Is This For Real estate / local service teams running outbound calls Agencies doing voice outreach and appointment setting Ops teams that want call logs + auto-booking in one place Setup Google Sheets Trigger:** select your spreadsheet Vapi_real-estate and tab call_list. VAPI Call:** set assistantId, phoneNumberId, and add Bearer token. Webhook:** copy the n8n webhook URL into VAPI so results post back. Google Calendar:** set the calendar ID (e.g., you@domain.com). Timezone:* the booking parser formats times to *Asia/Kolkata (IST)**. Batching:** adjust SplitInBatches size to control pace. ROI & Monetization Save 2–4 hours/week on manual dialing + data entry Faster follow-ups with instant booking creation Package as an “AI Caller + Auto-Booking” service ($1k–$3k/month) Strategy Insights In the full walkthrough, I show how to: Map VAPI tool call JSON safely into Sheets fields Handle missing/invalid times and default to safe slots Add no-answer / retry logic and opt-out handling Extend to send Slack/email alerts for hot leads Check Out My Channel For more voice automation workflows that turn leads into booked calls, check out my YouTube channel where I share the exact setups I use to win clients and scale to $20k+ monthly revenue.

📌 How to Set Up the AI UGC Video Automation System This system uses Telegram + N8N (no-code automation) + AI models to generate user-generated content (UGC) videos automatically. 🔹 Overview Input: Send a photo of the product + character via Telegram bot. Process: N8N workflow handles: Image analysis Prompt generation Image creation Video clip generation Combining clips into a final UGC ad Output: Video sent back to Telegram (or other destination like Google Drive/Dropbox). 🔹 System Workflow Input Section Telegram Setup: Create a Telegram bot and get its Bot ID. Connect the bot to N8N Telegram Trigger node. Bot listens for messages (photos + instructions). Send Input Upload one compressed image with : Product Character (optional) Example: “Create a UGC video with Gandalf promoting The Hobbit book. 20 seconds long.” Image Handling . N8N retrieves the image from Telegram (via file path). . OpenAI agent analyzes the image: . Extracts product details (brand, color, description). . Extracts character details (name, outfit, style). Confirm Input: . System replies on Telegram: “Got it. I’m now creating your video.” Step 1: Create Image AI Agent (Image Prompt) Generates a natural, UGC-style prompt (realistic iPhone photo look). Uses OpenAI GPT to structure prompt and aspect ratio (2:3 or 3:2). Image Generation Sends prompt + aspect ratio to Key.AI → 4.0 Image Model. Waits until image is generated. Example: Gandalf holding The Hobbit book. Step 2: Create Video Clips AI Agent (Video Prompt) Creates video script and scenes (dialogue + setting). Calculates how many clips needed (e.g. 20s request → 3 x 8s clips). Ensures UGC style (casual, amateur look). Clip Generation Sends prompts to Key.AI V3 model (Fast or Quality). Input: Prompt + image + aspect ratio. Output: Multiple short clips (8s each). Wait for Processing Clips take a few minutes to generate. Retrieve video URLs from Key.AI. Step 3: Combine Video Aggregate Clips 2.Collect all video URLs (from multiple clips). Merge with FFmpeg Send videos to File.AI → FFmpeg Merge Service. Stitches clips into one continuous video. Final Output Final merged video returned as a download URL. N8N sends the video back to your Telegram chat (or connected storage). 🔹 Customization Options Models: V3 Fast (~$0.40/clip, cheaper, good enough). V3 Quality (~$2/clip, slightly higher quality). Video Length: AI automatically adjusts number of clips. Outputs: Telegram (default) Can be extended to Google Drive, Dropbox, etc. 🔹 Cost Image generation: a few cents. Video clips: ~$0.40 each with V3 Fast. Clip merging: < $0.01. Much cheaper than manual UGC production.

🐱 MemeCoin Art Generator - using Gemini Flash NanoBanana & upload to Twitter Automatically generates memecoin art and posts it to Twitter (X) powered by Google Gemini, NanoBanana image generation, and n8n automation. 🧩 Overview This workflow creates viral style memecoin images (like Popcat) and posts them directly to Twitter with a witty, Gen Z style tweet. It combines text to image AI, scheduled triggers, and social publishing, all in one seamless flow. Workflow flow: Define your memecoin mascot (name, description, and base image URL). Generate an AI image prompt and a meme tweet. Feed the base mascot image into Gemini Image Generation API. Render a futuristic memecoin artwork using NanoBanana. Upload the final image and tweet automatically to Twitter. 🧠 Workflow Diagram ⚙️ Key Components | Node | Function | |------|-----------| | Schedule Trigger | Runs automatically at chosen intervals to start meme generation. | | Define Memecoin | Defines mascot name, description, and base image URL. | | AI Agent | Generates tweet text and creative image prompt using Google Gemini. | | Google Gemini Chat Model | Provides trending topic context and meme phrasing. | | Get Source Image | Fetches the original mascot image (e.g., Popcat). | | Convert Source Image to Base64 | Prepares image for AI based remixing. | | Generate Image using NanoBanana | Sends the prompt and base image to Gemini Image API for art generation. | | Convert Base64 to PNG | Converts the AI output to an image file. | | Upload to Twitter | Uploads generated image to Twitter via media upload API. | | Create Tweet | Publishes the tweet with attached image. | 🪄 How It Works 1️⃣ Schedule Trigger - starts the automation (e.g., hourly or daily). 2️⃣ Define Memecoin - stores your mascot metadata: memecoin_name: popcat mascot_description: cat with open mouth mascot_image: https://i.pinimg.com/736x/9d/05/6b/9d056b5b97c0513a4fc9d9cd93304a05.jpg 3️⃣ AI Agent - prompts Gemini to: Write a short 100 character tweet in Gen Z slang. Create an image generation prompt inspired by current meme trends. 4️⃣ NanoBanana API - applies your base image + AI prompt to create art. 5️⃣ Upload & Tweet - final image gets uploaded and posted automatically. 🧠 Example Output Base Source Image: Generated Image (AI remix): Published Tweet: Example tweet text: > Popcat's about to go absolutely wild, gonna moon harder than my last test score! 🚀📈 We up! #Popcat #Memecoin 🧩 Setup Tutorial 1️⃣ Prerequisites | Tool | Purpose | |------|----------| | n8n (Cloud or Self hosted) | Workflow automation platform | | Google Gemini API Key | For generating tweet and image prompts | | Twitter (X) API OAuth1 + OAuth2 | For uploading and posting tweets | 2️⃣ Import the Workflow Download memecoin art generator.json. In n8n, click Import Workflow → From File. Set up and connect credentials: Google Gemini API Twitter OAuth (Optional) Adjust Schedule Trigger frequency to your desired posting interval. 3️⃣ Customize Your MemeCoin In the Define Memecoin node, edit these fields to change your meme theme: memecoin_name: "doggo" mascot_description: "shiba inu in astronaut suit" mascot_image: "https://example.com/shiba.jpg" That’s it - next cycle will generate your new meme and post it. 4️⃣ API Notes Gemini Image Generation API Docs:** https://ai.google.dev/gemini-api/docs/image-generation#gemini-image-editing API Key Portal:** https://aistudio.google.com/api-keys

This template transforms uploaded brand assets into AI-generated influencer-style posts — complete with captions, images, and videos — using n8n, OpenAI, and your preferred image/video generation APIs. 🧠 Who it’s for Marketers, creators, or brand teams who want to speed up content ideation and visual generation. Perfect for social-media teams looking to turn product photos and brand visuals into ready-to-review creative posts. ⚙️ How it works Upload your brand assets — A form trigger collects up to three files: product, background, and prop. AI analysis & content creation — An OpenAI LLM analyzes your brand tone and generates post titles, captions, and visual prompts. Media generation — Connected image/video generation workflows create corresponding visuals. Result storage — All captions, image URLs, and video URLs are automatically written to a Google Sheet for review or publishing. 🧩 How to set it up Replace all placeholders in nodes: <<YOUR_SHEET_ID>> <<FILE_UPLOAD_BASE>> <<YOUR_API_KEY>> <<YOUR_N8N_DOMAIN>>/form/<<FORM_ID>> Add your own credentials in: Google Sheets HTTP Request AI/LLM nodes Execute the workflow or trigger via form. Check your connected Google Sheet for generated posts and media links. 🛠️ Requirements | Tool | Purpose | |------|----------| | OpenAI / compatible LLM key | Caption & idea generation | | Image/Video generation API | Creating visuals | | Google Sheets credentials | Storing results | | (Optional) n8n Cloud / self-hosted | To run the workflow | 🧠 Notes The workflow uses modular sub-workflows for image and video creation; you can connect your own generation nodes. All credentials and private URLs have been removed. Works seamlessly with both n8n Cloud and self-hosted setups. Output is meant for creative inspiration — review before posting publicly. 🧩 Why it’s useful Speeds up campaign ideation and content creation. Provides structured, reusable results in Google Sheets. Fully visual, modular, and customizable for any brand or industry. 🧠 Example Use Cases Influencer campaign planning Product launch creatives E-commerce catalog posts Fashion, lifestyle, or tech brand content ✅ Security & best practices No hardcoded keys or credentials included. All private URLs replaced with placeholders. Static data removed from the public JSON. Follows n8n’s template structure, node naming, and sticky-note annotation guidelines. 📦 Template info Name: AI-Powered Influencer Post Generator with Google Sheets and Image/Video APIs Category: AI / Marketing Automation / Content Generation Author: Palak Rathor Version: 1.0 (Public Release — October 2025)

This workflow automates company research and intelligence extraction from Glassdoor using Decode API for data retrieval and Google Gemini for AI-powered summarization. Who this is for This workflow is ideal for: Recruiters, analysts, and market researchers looking for structured insights from company profiles. HR tech developers and AI research teams needing a reliable way to extract and summarize Glassdoor data automatically. Venture analysts or due diligence teams conducting company research combining structured and unstructured content. Anyone who wants instant summaries and insights from Glassdoor company pages without manual scraping. What problem this workflow solves Manual Data Extraction**: Glassdoor company details and reviews are often scattered and inconsistent, requiring time-consuming copy-paste efforts. Unstructured Insights**: Raw reviews contain valuable opinions but are not organized for analytical use. Fragmented Company Data**: Key metrics like ratings, pros/cons, and FAQs are mixed with irrelevant data. Need for AI Summarization**: Business users need a concise, executive-level summary that combines employee sentiment, culture, and overall performance metrics. This workflow automates data mining, summarization, and structuring, transforming Glassdoor data into ready-to-use JSON and Markdown summaries. What this workflow does The workflow automates the end-to-end pipeline for Glassdoor company research: Trigger Start manually by clicking “Execute Workflow.” Set Input Fields Define company_url (e.g., a Glassdoor company profile link) and geo (country). Extract Raw Data from Glassdoor (Decodo Node) Uses the Decodo API to fetch company data — including overview, ratings, reviews, and frequently asked questions. Generate Structured Data (Google Gemini + Output Parser) The Structured Data Extractor node (powered by Gemini AI) processes raw data into well-defined fields: Company overview (name, size, website, type) Ratings breakdown Review snippets (pros, cons, roles) FAQs Key takeaways Summarize the Insights (Gemini AI Summarizer) Produces a detailed summary highlighting: Company reputation Work culture Employee sentiment trends Strengths and weaknesses Hiring recommendations Merge and Format Combines structured data and summary into a unified object for output. Export and Save Converts the final report into JSON and writes it to disk as C:\{{CompanyName}}.json. Binary Encoding for File Handling Prepares data in base64 for easy integration with APIs or downloadable reports. Setup Prerequisites n8n instance** (cloud or self-hosted) Decodo API credentials** (added as decodoApi) Google Gemini (PaLM) API credentials** Access to the Glassdoor company URLs Make sure to install the Decodo Community Node. Steps Import this workflow JSON file into your n8n instance. Configure your credentials for: Decodo API Google Gemini (PaLM) API Open the Set the Input Fields node and replace: company_url → with the Glassdoor URL geo → with the region (e.g., India, US, etc.) Execute the workflow. Check your output folder (C:\) for the exported JSON report. How to Customize This Workflow You can easily adapt this template to your needs: Add Sentiment Analysis** Include another Gemini or OpenAI node to rate sentiment (positive/negative/neutral) per review. Export to Notion or Google Sheets** Replace the file node with a Notion or Sheets integration for live dashboarding. Multi-Company Batch Mode** Convert the manual trigger to a spreadsheet or webhook trigger for bulk research automation. Add Visualization Layer** Connect the output to Looker Studio or Power BI for analytical dashboards. Change Output Format** Modify the final write node to generate Markdown or PDF summaries using the pypandoc or reportlab module. Summary This n8n workflow combines Decode web scrapping with Google Gemini’s reasoning and summarization power to build a fully automated Glassdoor Research Engine. With a single execution, it: Extracts structured company details Summarizes thousands of employee reviews Delivers insights in an easy-to-consume format Ideal for: Recruitment intelligence Market research Employer branding Competitive HR analysis

Document Analyzer and Q&A Workflow AI-powered document and web page analysis using n8n and GPT model. Ask questions about any local file or web URL and get intelligent, formatted answers. Who's it for Perfect for researchers, developers, content analysts, students, and anyone who needs quick insights from documents or web pages without uploading files to external services. What it does Analyzes local files**: PDF, Markdown, Text, JSON, YAML, Word docs Fetches web content**: Documentation sites, blogs, articles Answers questions**: Using GPT model with structured, well-formatted responses Input format: path_or_url | your_question Examples: /Users/docs/readme.md | What are the installation steps? https://n8n.io | What is n8n? Setup Import workflow into n8n Add your OpenAI API key to credentials Link the credential to the "OpenAI Document Analyzer" node Activate the workflow Start chatting! Customize Change AI model → Edit "OpenAI Document Analyzer" node (switch to gpt-4o-mini for cost savings) Adjust content length → Modify maxLength in "Process Document Content" node (default: 15000 chars) Add file types → Update supportedTypes array in "Parse Document & Question" node Increase timeout → Change timeout value in "Fetch Web Content" node (default: 30s)