AI: Ask questions about any data source (using the n8n workflow retriever)
This template aims to perform Q&A on data retrieved from another n8n workflow. Since that workflow can be used to retrieve any data from any service, this template can be used to ask questions about any data. It uses a manual trigger, various AI nodes, and an OpenAI Chat Model to extract and provide relevant information based on a specific query. Note that to use this template, you need to be on n8n version 1.19.4 or later.
By n8n TeamNarrating over a video using multimodal AI
This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip. This template was inspired by Processing and narrating a video with GPT's visual capabilities and the TTS API How it works Video is downloaded using the HTTP node. Python code node is used to extract the frames using OpenCV. Loop node is used o batch the frames for the LLM to generate partial scripts. All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it. The finished voiceover clip is uploaded to Google Drive. Sample the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing Requirements OpenAI for LLM Ideally, a mid-range (16GB RAM) machine for acceptable performance! Customising this workflow For larger videos, consider splitting into smaller clips for better performance Use a multimodal LLM which supports fully video such as Google's Gemini.
By JimleukBackup workflows to git repository on Github
Source code, I maintain this worflow here. Usage Guide This workflow backs up all workflows as JSON files named in the [workflow_name].json format. Steps Create GitHub Repository Skip this step if using an existing repository. Add GitHub Credentials In Credentials, add the GitHub credential for the repository owner. Download and Import Workflow Import this workflow into n8n. Set Global Values In the Globals node, set the following: repo.owner: GitHub username of the repository owner. repo.name: Name of the repository for backups. repo.path: Path to the folder within the repository where workflows will be saved. Configure GitHub Nodes Edit each GitHub node in the workflow to use the added credentials. Workflow Logic Each workflow run handles files based on their status: New Workflow If a workflow is new, create a new file in the repository. Unchanged Workflow If the workflow is unchanged, skip to the next item. Changed Workflow If a workflow has changes, update the corresponding file in the repository. Current Limitations / Needs work Name Change of Workflows If a workflow is renamed or deleted in n8n, the old file remains in the repository. Deleted Workflows Deleted workflows in n8n are not removed from the repository.
By ShashikanthReceive email updates via IMAP
Companion workflow for IMAP Email node docs
By amudhanGenerate tailored interview questions with GPT-4 based on CV, JD, and round
๐ค Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round Watch the demo video below: [](https://youtu.be/-KHze-bRpqQ) ๐ Whoโs it for This workflow is designed for: Recruiters and Talent Acquisition Specialists who want to automate candidate interview prep. Hiring Managers conducting multiple interviews and needing personalized question sets. Technical Interviewers who want to save time and be well-prepared with relevant questions. โ๏ธ How it works / What it does The Smart Interview Assistant automates the interview preparation process in a few clicks: Accepts: Multiple resumes (PDFs) Selected job role Chosen interview round Extracts structured data from: The candidateโs CV The corresponding Job Description (JD) Uses GPT-4 to analyze: Candidate profile Role requirements Interview round context Generates: Tailored interview questions Expected answers A summarized interview prep report Sends the report directly to the hiring team via email (SMTP) ๐ Google Drive Structure ๐ Root Folder โโโ ๐ jd/ Stores all job descriptions in PDF format โ โโโ Backend_Engineer.pdf โ โโโ AzureDevOpsLead.pdf โ โโโ ... โโโ ๐ Positions (Google Sheet) Maps Job Role โ JD File Link ๐ Sample Mapping Sheet: Positions Sheet Columns: Job Role Job Description File URL (pointing to PDF in jd/ folder) ๐ ๏ธ How to Set Up Step 1: Configure API Integrations โ Connect your OpenAI GPT-4 API Key โ Enable Google Cloud APIs: Google Sheets API (to read job roles) Google Drive API (to access CV and JD files) โ Set up SMTP credentials (for email delivery) Step 2: Prepare Google Drive & Mapping Sheet Create a root folder on Google Drive Inside the root folder: Create a folder named /jd/ and upload all job descriptions (PDFs) Create a Google Sheet named Positions with the following format: | Job Role | Job Description File URL | |-----------------------------|--------------------------------------------| | Azure DevOps Engineer | https://drive.google.com/xxx/jd1.pdf | | Full-Stack Developer (.NET) | https://drive.google.com/xxx/jd2.pdf | Step 3: Build the Application Form Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects: ๐ Resume file (PDF) ๐งพ Job Role (dropdown) ๐ Interview Round (dropdown) Step 4: Resume & JD Extraction ๐ Use Extract from PDF to parse the resume content ๐ Retrieve the JD link from the Positions sheet based on the selected Job Role ๐ Use Download file to pull the PDF for processing Step 5: Analyze with GPT-4 Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output) Merge results Add manual input or mapping for the Interview Round metadata Step 6: Generate Interview Report Use a second GPT-4 agent (e.g., HR Expert Agent) to: Generate 6โ8 tailored interview questions Include expected answers and rationale Step 7: Deliver Final Report Format the content as: ๐ PDF (optional) ๐จ Email body Send the report to the recruiter, hiring manager, or interviewer via SMTP โ Requirements ๐ OpenAI GPT-4 API Key ๐ Google Drive (for resume and JD storage) ๐ Google Sheet (job role mapping) ๐ฌ SMTP credentials (host, username, password) ๐งฐ n8n self-hosted or cloud instance with: PDF Parser Google Sheets node HTTP Download node Email node โ๏ธ How to Customize the Workflow | Part | Customization Options | |----------------------------|-------------------------------------------------------------| | Form UI | Modify the design, dropdown options, or input validations | | Job Description Source | Replace Google Sheet with Notion, Airtable, or database | | Interview Metadata | Add job level, region, or language preference | | AI Prompt Tuning | Adjust prompt phrasing or temperature in GPT nodes | | Report Format | Generate PDF instead of email body using PDF node | | Delivery Method | Add internal HR portal webhook or generate downloadable link |
By Trung TranTesla 1day indicators tool (Macro-Level Technical AI)
๐ Analyze Teslaโs daily trading structure with AI using 6 Alpha Vantage indicators. This tool evaluates long-term trend health, volatility patterns, and potential reversal signals at the 1-day timeframe. Designed for use within the Tesla Financial Market Data Analyst Tool, this agent helps swing and position traders anchor macro sentiment. โ ๏ธ Not standalone. Must be executed via Execute Workflow ๐ Requires: Tesla Quant Technical Indicators Webhooks Tool Alpha Vantage Premium API Key OpenAI GPT-4.1 credentials --- ๐ What It Does This tool queries a secured webhook (/1dayData) to retrieve real-time, trimmed JSON data for: RSI (Relative Strength Index) BBANDS (Bollinger Bands) SMA (Simple Moving Average) EMA (Exponential Moving Average) ADX (Average Directional Index) MACD (Moving Average Convergence Divergence) These values are then passed to a LangChain AI Agent powered by GPT-4.1, which returns: A 2โ3 sentence market condition summary Structured indicator values Timeframe tag ("1d") --- ๐ Sample Output json { "summary": "TSLA shows consolidation on the daily chart. RSI is neutral, BBANDS are contracting, and MACD is flattening.", "timeframe": "1d", "indicators": { "RSI": 51.3, "BBANDS": { "upper": 192.80, "lower": 168.20, "middle": 180.50, "close": 179.90 }, "SMA": 181.10, "EMA": 179.75, "ADX": 15.8, "MACD": { "macd": -0.25, "signal": -0.20, "histogram": -0.05 } } } --- ๐ง Agent Components | Component | Description | | ----------------------------- | -------------------------------------------------- | | 1day Data (HTTP Node) | Pulls latest data from secured /1dayData webhook | | OpenAI Chat Model | GPT-4.1 powers the analysis logic | | Tesla 1day Indicators Agent | LangChain agent performing interpretation | | Simple Memory | Short-term session continuity | --- ๐ ๏ธ Setup Instructions Import Workflow into n8n Name: Tesla1dayIndicators_Tool Add Required Credentials Alpha Vantage Premium (via HTTP Query Auth) OpenAI GPT-4.1 (Chat Model) Install Webhook Fetcher Required: Tesla Quant Technical Indicators Webhooks Tool Endpoint /1dayData must be active Execution Context This tool is only triggered via: ๐ Tesla Financial Market Data Analyst Tool Inputs expected: message: optional context sessionId: session memory linkage --- ๐ Sticky Notes Overview ๐ Tesla 1-Day Indicators Tool โ Purpose and integration ๐ก Webhook Fetcher โ Pulls daily Alpha Vantage data via HTTPS ๐ง GPT-4.1 Model โ Reasoning for trend classification ๐ Sub-Agent Trigger โ Used only by Financial Market Analyst ๐ง Memory Buffer โ Ensures consistent session logic --- ๐ Licensing & Support ยฉ 2025 Treasurium Capital Limited Company This workflowโincluding prompts, logic, and formattingโis protected IP. ๐ Don Jayamaha โ LinkedIn ๐ Creator Profile --- ๐ Evaluate long-term Tesla price behavior with AI-enhanced technical analysisโcritical for swing trading strategy. Required by the Tesla Financial Market Data Analyst Tool.
By Don Jayamaha JrAutomate hotel booking requests from Gmail to Google Sheets with GPT-5-mini
Whoโs it for This workflow is for hotel managers, travel agencies, and hospitality teams who receive booking requests via email. It eliminates the need for manual data entry by automatically parsing emails and attachments, assigning booking cases to the right teams, and tracking performance metrics. What it does This workflow goes beyond simple automation by including enterprise-grade logic and security: ๐ก๏ธ Gatekeeper: Watches your Gmail and filters irrelevant emails before spending money on AI tokens. ๐ง AI Brain: Uses OpenAI (GPT-5-mini) to extract structured data from unstructured email bodies and PDF attachments. โ๏ธ Business Logic: Automatically routes tasks to different teams based on urgency, room count, and VIP status. ๐ Security: Catches PII (like credit card numbers) and scrubs them before they hit your database. ๐จ Safety Net: If anything breaks, a dedicated error handling path logs the issue immediately so no booking is lost. ๐ ROI Tracking: Calculates the time saved per booking to prove the value of automation. How to set up Create your Google Sheet: Create a new sheet and rename the tabs to: Cases, Team Assignments, Error Logs, Success Metrics. Add Credentials: Go to n8n Settings โ Credentials and add your Gmail (OAuth2), Google Sheets, and OpenAI API keys. Configure User Settings: Open the "Configuration: User Settings" node at the start of the workflow. Paste your specific Google Sheet ID and Admin Email there. Adjust Business Rules: Open the "Apply Business Rules" node (Code node) to adjust the logic for team assignment (e.g., defining what counts as a "VIP" booking). Customize Templates: Modify the email templates in the Gmail nodes to match your hotel's branding. Test: Send a sample booking email to yourself to verify the filters and data extraction. Setup requirements Gmail account (OAuth2 connected) Google Sheets (with the 4 tabs listed below) OpenAI API key (GPT-5-mini recommended) n8n Cloud or self-hosted instance How to customize Filter Booking Emails: Update the trigger node keywords to match your specific email subjects (e.g., "Reservation", "Booking Request"). Apply Business Rules: Edit the Javascript in the Code node to fit your companyโs internal logic (e.g., changing priority thresholds). New Metrics: Add new columns in the Google Sheet (e.g., โRevenue Metricsโ) and map them in the "Update Sheet" node. AI Model: Switch to GPT-5 if you need higher reasoning capabilities for complex PDF layouts. Google Sheets Structure Description This workflow uses a Google Sheets document with four main tabs to track and manage hotel booking requests. Cases This is the main data log for all incoming booking requests. case_id: Unique identifier generated by the workflow. processed_date: Timestamp when the workflow processed the booking. travelagency / contactdetails: Extracted from the email. numberofrooms / checkindate: Booking details parsed by the AI. special_requests: Optional notes (e.g., airport transfer). assigned_team / priority: Automatically set based on business rules. daysuntilcheckin: Dynamic field showing urgency. Team Assignments Stores internal routing and assignment details. timestamp: When the case was routed. case_id: Link to the corresponding record in the Cases tab. assignedteam / teamemail: Which department handles this request. priority: Auto-set based on room count or urgency. Error Log A critical audit trail that captures details about any failed processing steps. errortype: Categorization of the failure (e.g., MISSINGREQUIRED_FIELDS). error_message: Detailed technical explanation for debugging. original_sender / snippet: Context to help you manually process the request if needed. Success Metrics Tracks the results of your automation to prove its value. processingtimeseconds: The time savings achieved by the automation (run time vs. human time). record_updated: Confirmation that the database was updated. ๐ Support If you encounter any issues during setup or have questions about customization, please reach out to our dedicated support email: foivosautomationhelp@gmail.com
By GtarasCreate AI personalized video & voice outreach with HeyGen, ElevenLabs & Perplexity
Automated Sales Rep Clone Outreach Video and Voice Note for B2B Outbound This workflow automatically transforms new leads from Google Sheets into hyper-personalized outreach videos, voice notes, and emails using AI research, scriptwriting, video cloning, and voice generation. Perfect for SDRs, founders, and agencies who want to scale outreach without sacrificing personalization. ๐ฅ Watch step by step build: https://www.youtube.com/watch?v=q9AAh9zRou4 What this template does Whenever a new row is added to your Google Sheets CRM, this workflow: Reads the new lead (Name, Email, Phone, Company, Industry, LinkedIn URL) Runs deep research on the person & company using Perplexity Generates a personalized 30-second outreach script Creates a cloned-face, AI-generated HeyGen video with the script Creates an ElevenLabs voice note using the same personalized insights Uploads the audio file to Google Drive Sends an email to yourself containing: Outreach subject line Email body Personalized video link Personalized voice note link (Optional) Sends a WhatsApp/SMS/MMS message via Twilio with the files or links This template builds a complete AI-powered outbound engineโresearch, video, voice note, and emailโfully automated. Why this is useful Turns manual outbound into a hands-free, 360ยฐ AI workflow Personalized video outreach dramatically increases reply rates Consistent research quality for every lead SDRs save hours per day on manual prep Perfect for: Influencer agencies SaaS outbound teams Founders doing cold outreach Recruitment agencies Real estate & service businesses Requirements Before running this workflow, connect: Google Sheets OAuth (trigger + CRM sheet) Perplexity API Key OpenAI API Key (GPT-5.1, GPT-4.1-mini) OpenRouter API Key HeyGen API Key (for video avatar) ElevenLabs API Key (for voice note) Google Drive OAuth (for file upload) Twilio credentials (optional SMS/WhatsApp) โ ๏ธ All credentials must be added manually after importing. This ensures security and complies with n8n Template Guidelines. How it works (Node Breakdown) Google Sheets Trigger Watches your CRM sheet and fires whenever a new lead row is added. Code Node โ Extract Latest Row Ensures only the newly added row continues through the workflow. Research Agent Powered by OpenAI + Perplexity Scrapes professional history, company insights, marketing gaps Identifies outreach opportunities & triggers Produces a structured research summary Scripting Agent Writes a natural, human-sounding 30-second outreach script tailored to that exact lead. HeyGen Video Generator Creates a personalized avatar video narrating the script (720ร1280). ElevenLabs Voice Generation Generates a custom voice note version of the pitch. Google Drive Upload Saves the voice note file for sharing or sending via WhatsApp. Twilio Message (optional) Sends the voice note or video link via SMS/WhatsApp. Email Output Creates a fully structured JSON email including: Subject line Personalized body HeyGen video link Voice note link Delivered via Gmail node. Setup (Step-by-Step) Import the template into n8n Open Google Sheets Trigger โ choose your CRM sheet Add all required credentials: Perplexity OpenAI OpenRouter HeyGen ElevenLabs Google Drive Gmail Twilio (optional) In HeyGen node, choose: Your avatar Your preferred voice ID In ElevenLabs node, set: Your preferred voice model Review the system prompts of: Research Agent Script Agent Email Agent Adjust for your brand tone if needed. Run once manually to test. Turn on the workflowโyour AI outbound engine is live. Customization Ideas Swap HeyGen avatar to match your brand identity Add a Slack notification when each video is ready Save research & scripts into a Notion database Create a HubSpot contact for each lead Add duplicate detection logic Auto-post video to social channels for public outreach Troubleshooting Video stuck in โprocessingโ? โ Increase the Wait node duration (30โ60 sec). Voice note too robotic? โ Switch to a premium ElevenLabs voice. Research not specific enough? โ Strengthen the system prompt with more constraints. Emails not arriving? โ Ensure Gmail OAuth has send permission configured. API authentication errors? โ Check credentials in each node (OpenAI, Perplexity, HeyGen, etc.).
By Automate With MarcWhatsApp receipt OCR & AI data extraction with Twilio, LlamaParse & Gemini
WhatsApp Receipt OCR & Data Extraction Suite Categories: Accounting Automation โข OCR Processing โข AI Data Extraction โข Business Tools This workflow transforms WhatsApp into a fully automated receipt-processing system using advanced OCR, multi-model AI parsing, and structured data storage. By combining LlamaParse, Claude (OpenRouter), Gemini, Google Sheets, and Twilio, it eliminates manual data entry and delivers instant, reliable receipt digitization for any business. --- What This Workflow Does When a user sends a receipt photo or PDF via WhatsApp, the automation: Receives the file through Twilio WhatsApp Uploads and parses it with LlamaParse (high-res OCR + invoice preset) Extracts structured data using Claude + Gemini + a strict JSON parser Cleans and normalizes the data (dates, ABN, vendor, tax logic) Uploads the receipt to Google Drive Logs the extracted fields into a Google Sheet Replies to the user on WhatsApp with the extracted details Asks for confirmation via quick-reply buttons Updates the Google Sheet based on user validation The result is a fast, scalable, human-free system for converting raw receipt photos into clean, structured accounting data. --- Key Benefits No friction for users: receipts are submitted simply by sending a WhatsApp message. High-accuracy OCR: LlamaParse extracts text, tables, totals, vendors, tax, and ABN with impressive reliability. Enterprise-grade data validation: complex logic ensures the correct interpretation of GST, included taxes, or unidentified tax amounts. Multi-model extraction: Claude and Gemini both analyse the OCR output for more reliable result. We have one primary LLM and a secondary one. Hands-off accounting: every receipt becomes a standardized row in Google Sheets. Two-way WhatsApp communication: users can confirm or reject extracted data instantly. Scalable architecture: perfect for businesses handling dozens or thousands of receipts monthly. --- How It Works (Technical Overview) Twilio โ Webhook Trigger The workflow starts when a WhatsApp message containing a media file hits your Twilio webhook. Initial Google Sheets Logging The MessageSid is appended to your tracking sheet to ensure every receipt is traceable. LlamaParse OCR The file is sent to LlamaParse with the invoice preset, high-resolution OCR, and table extraction enabled. The workflow checks job completion before moving further. LLM Data Extraction The OCR markdown is analyzed using: Claude Sonnet 4.5 (via OpenRouter) Gemini 2.5 Pro A strict structured JSON output parser Custom JS cleanup logic The system extracts: Vendor Cost Tax (with multi-rule Australian GST logic) Currency Date (parsed + normalized) ABN (validated and digit-normalized) Google Drive Integration The uploaded receipt is stored, shared, and linked back to the record in Sheets. Google Sheets Update Fields are appended/updated following a clean schema: Vendor Cost Tax Date Currency ABN Public drive link Status (Confirmed / Not confirmed) User Response Flow The user receives a summary of extracted data via WhatsApp. Buttons allow them to approve or reject accuracy. The Google Sheet updates accordingly. --- Target Audience This workflow is ideal for: Accounting & bookkeeping firms Outsourced finance departments Small businesses tracking expenses Field workers submitting receipts Automation agencies offering DFY systems CFOs wanting real-time expense visibility --- Use Cases Expense reconciliation Automated bookkeeping Receipt digitization & compliance Real-time employee expense submission Multi-client automation at accounting agencies --- Required Integrations Twilio WhatsApp (Business API number + webhook) LlamaParse API OpenRouter (Claude Sonnet) Google Gemini API Google Drive Google Sheets --- Setup Instructions (High-Level) Import the n8n workflow. Connect your Twilio WhatsApp account. Add API credentials for: LlamaParse OpenRouter Google Gemini Google Drive Google Sheets Create your target Google Sheet. Configure your WhatsApp webhook URL in Twilio. Test with a sample receipt. --- Why This System Works Users send receipts using a tool they already use daily (WhatsApp). LlamaParse provides state-of-the-art OCR for low-quality receipts. Using multiple LLMs drastically increases accuracy for vendor, ABN, and tax extraction. Advanced normalization logic ensures data is clean and accounting-ready. Google Sheets enables reliable storage, reporting, and future integrations. End-to-end automation replaces hours of manual work with instant processing. --- Watch My Complete Build Process Want to see exactly how I built this entire AI design system from scratch? I walk through the complete development process on my YouTube channel
By Gabriela Macovei