Workflow Templates

Automated Trade Report from Interactive Brokers This workflow is aimed at traders who use Interactive Brokers. It automatically retrieves the trades made in IBKR on a daily basis and writes them to a Google Sheet, so that anyone can easily perform further analyses and statistics using the on-board tools. This creates an automatic, continuous trade journal. Typical Usecaes Monitoring your trades in one journal Analyze your Profit & Losses Basis for any kind of statistics • Log trades (entry, exit, setup, reason) • Analyze performance (win rate, R/R, expectancy) • Evaluate strategies & setups • Detect mistakes & patterns • Track emotions & discipline • Support coaching, reviews & improvement How it works A daily schedule triggers a FlexStatement request to Interactive Brokers to start generating a trade report. The workflow extracts the reference code from IBKR's response, waits for the report to be ready, then downloads the Flex report XML. The XML is parsed and split into individual Trade records. Key fields (tradeDate, symbol, quantity, buySell, tradeID, price, money, currency, fxRateToBase) are normalized.\n5. Each trade is appended or updated in the configured Google Sheet, matching on tradeID to avoid duplicates and keep the journal current. Prerequisites Trading Account on IBKR Google Sheets OAuth2 A Google Sheet containing your trading journal Setup [ ] Set schedule to run at your desired time (default: 08:00) [ ] Add or verify IBKR request token/reference parameters. 1. Create Flex Query Token: Go to IBKR Account Management Reports → Flex Queries → Flex Web Service → Generate Current Token → Make a note of the token (e.g.: 123456789012345678901234) 2. Enter Flex Token: In node '1. Request Flex Report' and in node '2. Extract Reference Code' Replace YOUR_FLEX_TOKEN with your token ID 3. Create Flex Query in IBKR (if not already done): Go to IBKR Account Management Reports → Flex Queries → Activity Flex Query → Create Select: Trade Confirmation ✓ Period: Last 365 Days Format: XML Save and note down the query ID 4. Enter Flex Query ID: In node '1. Request Flex Report' Replace YOUR_QUERY_ID with your query ID [ ] Adjust wait time if IBKR needs longer to generate reports [ ] Select the Google Sheet and target sheet/tab [ ] Connect Google Sheets OAuth2 account [ ] Confirm column mapping and that tradeID is the matching column [ ] Run a manual test to validate parsing and row updates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works Using chat node, ask a question pertaining to information stored in your MySQL database AI Agent converts your question to a SQL query AI Agent executes the SQL query and returns a result AI Agent can remember the previous 5 questions How to set up: Add your OpenAI API Key in "OpenAI Chat Model" node Add your MySQL credentials in the "SQL DB - List Tables and Schema" and "Execute a SQL Query in MySQL nodes" Update the database name in "SQL DB - List Tables and Schema" node. Replace "your_query_name" under the Query field with your actual database name After the above steps are completed, use the "When chat message received" node to ask a question about your data using plain English

How it works: This template takes approved Notion pages and syncs them to a Webflow CMS collection as draft items. It reads pages marked Status = Ready for publish in a specific Notion database/project, merges JSON content stored across page blocks into a single object, then either creates a new CMS item or updates the existing one by name. On success it sets the Notion page to 5. Done; on failure it switches the page to On Hold for review.  Step-by-step: Manual Trigger You start the run with When clicking ‘Execute workflow’. Get Notion Pages (Notion → Database: Tech Content Tasks) Pull all pages with Status = Ready for publish scoped to the target Project. Loop Over Items (Split In Batches) Process one Notion page at a time. Code (Pass-through) Expose page fields (e.g., name, id, url, sector) for downstream nodes. Get Notion Block (children) Fetch all blocks under the page id. Merge Content (Code) Concatenate code-block fragments, parse them into one mergedContent JSON, and attach the page metadata. Get Webflow Items (HTTP GET) List items in the target Webflow collection to see if an item with the same name already exists. Update or Create (Switch) No match: Create Webflow Item (POST) with isDraft: true, mapping all fieldData (e.g., category titles, meta title, excerpt, hero copy/image, benefits, problem pointers, FAQ, ROI). Match: Update Webflow Item (Draft) (PATCH) for that id. Keep the existing slug, write latest fieldData, leave isDraft: true. Write Back Status (Notion) Success path → set Status = 5. Done. Error path → set Status = On Hold. Log Submission (Code) Log a compact object with status, notionPageId, webflowItemId, timestamp, and action. Wait → Loop Short pause, then continue with the next page. Tools integration: Notion** — source database and page blocks for approved content. Webflow CMS API* — destination collection; items created/updated as *drafts**. n8n Code** — JSON merge and lightweight logging. Split In Batches + Wait** — controlled, item-wise processing. Want hands-free publishing? Add a Cron trigger before step 2 to run on a schedule.

Product Ingredient Safety Analyzer with AI via WhatsApp What does this workflow do? This workflow creates an intelligent WhatsApp bot that analyzes product ingredients and provides instant safety assessments. Users can send either text queries (product names/brands) or images of product labels, and receive AI-powered analysis covering food, cosmetics, personal care, pharmaceuticals, and household products. Who's it for? Health-conscious consumers** wanting to make informed purchasing decisions Parents** checking product safety for their children People with allergies or sensitivities** screening for harmful ingredients Beauty and skincare enthusiasts** verifying cosmetic product safety Wellness coaches or nutritionists** helping clients evaluate products Small business owners** offering product safety consultation services Eco-conscious consumers** checking for environmental toxins Anyone** looking to understand what's in their everyday products What do you need to get started? Required Accounts & APIs: WhatsApp Business API** - For receiving and sending messages Google Cloud Account** - For Document AI (OCR) service Google Gemini API** - For AI-powered ingredient analysis Setup Steps: Configure WhatsApp Business API credentials Enable Google Document AI in your Google Cloud project Create a Document AI processor for OCR Set up Google Gemini API access Configure all credentials in N8N How does this workflow work? User Input Options: Text Messages**: Send product name/brand (e.g., "Dove soap", "Coca Cola") Images**: Upload photos of product ingredient labels Conversational**: Ask questions or request help Processing Flow: For Image Messages: WhatsApp receives image message Extracts and downloads the image Converts image to Base64 format Uses Google Document AI OCR to extract text AI analyzes extracted text + user caption Returns safety assessment via WhatsApp For Text Messages: WhatsApp receives text query AI directly analyzes product name/ingredients Returns safety assessment via WhatsApp AI Analysis Includes: Product type identification (food, cosmetic, pharmaceutical, etc.) Harmful ingredient detection (parabens, sulfates, trans fats, etc.) Beneficial ingredient highlights Clear safety verdict: ✅ SAFE / ⚠️ CAUTION / ❌ AVOID Practical recommendations and alternatives Response Format: The AI provides concise, WhatsApp-friendly messages with: Product category and type Key ingredients found Safety concerns with specific flags Clear recommendation Actionable advice Use Cases Health-conscious consumers** checking food product ingredients Beauty enthusiasts** verifying cosmetic safety Parents** ensuring child product safety People with allergies** screening for harmful ingredients Eco-conscious users** checking for environmental toxins General wellness** making informed purchase decisions Key Features Dual input support**: Text and image processing OCR technology**: Extracts text from product labels Multi-category analysis**: Food, cosmetics, pharmaceuticals, household items Conversational AI**: Handles greetings, help requests, unclear queries Mobile-optimized**: WhatsApp-friendly formatting Instant results**: Real-time safety assessments Educational**: Explains why ingredients are safe or harmful Technical Highlights Smart routing**: Automatically detects message type (text vs image) Structured output**: JSON-formatted AI responses for reliability Product-specific criteria**: Different analysis standards per category Error handling**: Requests clearer images if OCR fails Conversational fallback**: Guides users when information is insufficient Example Interactions User sends image of shampoo bottle: Response: "Hair Care Product Analysis - Contains sulfates and parabens. ⚠️ USE WITH CAUTION. Consider sulfate-free alternatives for healthier hair." User texts "Maggi noodles": Response: "Food Product Analysis - High sodium content, contains MSG and artificial colors. ❌ AVOID REGULAR CONSUMPTION. Occasional treat okay." User texts "Hi": Response: "Hi! I'm your Product Safety Analyzer. Send me a product name or photo of ingredients to check safety!" Benefits Empowers informed decisions**: Know what you're consuming/using Saves research time**: Instant analysis vs manual ingredient lookup Accessible**: Works via familiar WhatsApp interface Comprehensive**: Covers multiple product categories Educational**: Learn about ingredient safety over time Convenient**: Analyze products while shopping Notes OCR works best with clear, well-lit images AI provides general safety information, not medical advice Analysis based on commonly known ingredient safety standards Users should consult professionals for specific health concerns Supports conversational queries for better user experience

This workflow streamlines accounts receivable management by automatically monitoring invoices in Google Sheets and sending scheduled payment reminders. It is designed for businesses using Gmail and Google Sheets that need a scalable alternative to complex accounting software. How it works Watches for invoices: Triggers daily or via form submission to check for new entries. First Follow-up (Day 7): Checks payment status one week after the invoice date. If unpaid, it sends a friendly email (and optional SMS). Second Follow-up (Day 9): Re-checks status and sends a firmer reminder if funds are still not received. Final Notice (Day 12): Sends a final urgent reminder before closing the cycle. Smart Stopping: The workflow checks the 'Payment Status' column before every single message to ensure clients who have already paid are never disturbed. Setup time: About 20 minutes. Prerequisites: A Google Sheet with columns for Date, Email, and Payment Status.

Description Automatically scan your Stripe customers daily to detect duplicates and keep your customer database clean. This workflow uses advanced fuzzy matching for emails and names, logs results to Airtable for review, and notifies your team in Slack with actionable insights. 💳🧹💬 What This Template Does Runs every day at 2:00 AM via scheduled trigger ⏰ Fetches all customers from Stripe 💳 Analyzes for potential duplicates using email and name similarity 🔍 Logs duplicate suggestions into Airtable for review 📊 Sends formatted Slack notifications with detailed reports 💬 Key Benefits Keeps your Stripe customer database clean and deduplicated 🧹 Reduces errors in reporting and billing 💵 Provides confidence scoring for duplicate matches 🔑 Centralized review and approval in Airtable 📋 Real-time team notifications in Slack with actionable insights 📲 Features Daily 2 AM schedule with cron expression 0 2 * * * Email-based duplicate detection 📧 Name similarity matching using Levenshtein distance 👤 Smart grouping: oldest record becomes the primary 🏷️ Logs duplicates to Airtable with status tracking 🔄 Slack notifications with statistics, match types, and Airtable link ⚡ Requirements n8n instance (cloud or self-hosted) Stripe API credentials with customer read access Airtable account with a table for duplicate tracking Slack App & Bot Token with chat:write permission Target Audience SaaS companies managing large Stripe customer databases 🏢 Finance and billing teams wanting clean records 💰 Support teams reducing customer confusion from duplicates 🎧 Growth and marketing teams ensuring CRM accuracy 📈 Any business that relies on Stripe for recurring billing 💼 Step-by-Step Setup Instructions Set up Stripe API credentials in n8n (use your Secret Key). Create an Airtable base and table with required fields (Customer IDs, Email, Similarity Score, Status). Add Slack API credentials and choose your target channel. Replace environment variables for Airtable (AIRTABLE_BASE_ID, AIRTABLE_TABLE_ID) and Slack (SLACK_CHANNEL_ID). Import this workflow into n8n and connect your credentials. Run the workflow once manually to validate data flows. Enable the workflow for daily automated duplicate detection. ✅

What It Does Build your own AI Chatbot that listens, thinks, searches, and speaks — all inside n8n. This template combines Groq AI, LangChain Agent, SerpAPI, and StreamElements TTS to create a chatbot that: Understands natural language input Searches the web for real-time answers Remembers previous messages (context memory) Replies with a realistic AI voice How It Works Chat Trigger: The workflow activates whenever a new message is received. Groq AI Agent: Processes user input, performs reasoning, and integrates with SerpAPI for live web results. Memory Node: Keeps the chat context for a natural conversation flow. TTS Node: Converts AI responses into realistic voice replies using StreamElements API. Setup Steps Connect your Groq, SerpAPI, and StreamElements credentials (no coding required). Customize the chatbot behavior directly inside n8n. Deploy instantly and chat via webhook or UI widget. Use Cases Voice-enabled customer-support bots AI chat widgets for websites Personal assistants that talk and search the web

This n8n template turns raw call transcripts into clean HubSpot call logs and a single, actionable follow-up task—automatically. Paste a transcript and the contact’s email; the workflow finds the contact, summarizes the conversation in 120–160 words, proposes the next best action, and (optionally) updates missing contact fields. Perfect for reps and founders who want accurate CRM hygiene without the manual busywork. How it works A form trigger collects two inputs: Contact email Plain-text call transcript The workflow looks up the HubSpot contact by email to pull known properties. An AI agent reads the transcript (plus known fields) to: Extract participants, role, problem/opportunity, requirements, blockers, timeline, and metrics. Write a 120–160 word recap a teammate can skim. Generate one concrete follow-up task (title + body). Suggest updates for missing contact properties (city, country, job title, job function). The recap is logged to HubSpot as a completed Call engagement. The follow-up is created in HubSpot as a Task with subject and body. (Optional) The contact record is updated using AI-suggested values if the transcript clearly mentions them. How to use Connect HubSpot (OAuth2) on all HubSpot nodes. Connect OpenAI on the AI nodes. Open Form: Capture Transcript, submit the email + transcript. (Optional) In AI: Summarize Call & Draft Task, tweak prompt rules (word count, date normalization). (Optional) In Update Contact from Transcript, review the mapped fields before enabling in production. Activate the workflow and paste transcripts after each call. Requirements HubSpot** (OAuth2) for contact search, call logging, and tasks OpenAI** for summarization and task drafting Notes & customization ideas Swap the form for a Google Drive or S3 watcher to ingest saved transcripts. Add a speech-to-text step if you store audio recordings. Extend Update Contact to include additional fields (timezone, department, seniority). Post the summary to Slack or email the AE for quick handoffs. Gate updates with a confidence check, or route low-confidence changes for manual approval.

N8N Workflow: Send and Check TTS (Text-to-speech) Voice Calls with Email Verification This workflow automates a two-factor verification process using a voice call and an email. It is designed to send a text-to-speech (TTS) voice call with a verification code and, upon successful voice verification, to send an email with a second verification code. How it Works This workflow automates the process of sending voice calls for verification and combines it with email verification. It uses the ClickSend API for the voice call and an SMTP integration for sending the email. Use Cases Two-factor authentication (2FA) for user registration or login. Automated verification for phone numbers and email addresses. Building a custom verification system for web applications. Setup Instructions ClickSend API: Register on ClickSend and obtain your API Key. In the Send Voice node, create a Basic Auth credential using your ClickSend username and API Key as the password. SMTP Credentials: In the Send Email node, you must set up your SMTP credentials for the sender's email. Workflow Logic Trigger: The workflow is started by submitting a form. Set Voice Code: The workflow sets a predefined voice verification code. Send Voice Call: A voice call is made to the provided phone number using the ClickSend API, where a synthesized voice reads the code. Verify Voice Code: A form appears to prompt the user to enter the voice code they received. Conditional Check: An If node checks if the entered voice code is correct. Set Email Code & Send Email: If the voice code is correct, a second code is set, and an email is sent to the user with that code. Verify Email Code: The user is then prompted to enter the code from the email. Final Check: A final If node verifies the email code. The workflow either leads to a Success message or a Fail email code message. Node Descriptions | Node Name | Description | |-----------|-------------| | On form submission | This trigger node presents a form to the user to collect their phone number, desired voice, language, email, and name. | | Set voice code | A Set node that defines the verification code for the voice call. | | Code for voice | A Code node that adds spaces between the digits of the voice code to make it sound clearer during the call. | | Send Voice | This httpRequest node sends a POST request to the ClickSend API to initiate the TTS voice call. | | Verify voice code | A form node that prompts the user to enter the code they received via the voice call. | | Is voice code correct? | An If node that checks if the code entered by the user matches the predefined voice code. | | Set email code | A Set node that defines the verification code for the email. | | Send Email | This node uses an SMTP credential to send an email to the user with their verification code. | | Verify email code | A form node that prompts the user to enter the code they received via email. | | Is email code correct? | An If node that checks if the code entered by the user matches the predefined email code. | | Success | A form node that displays a success message upon completion of both verifications. | | Fail voice code | A form node that displays a failure message if the voice code is incorrect. | | Fail email code | A form node that displays a failure message if the email code is incorrect. | Customization Tips You can change the verification codes by modifying the values in the Set voice code and Set email code nodes. The form can be customized to change the fields, labels, and dropdown options for voice and language. The email content and subject can be customized in the Send Email node. Suggested Sticky Notes for Workflow STEP 1**: "Register here to ClickSend and obtain your API Key... In the node 'Send Voice' create a 'Basic Auth' with the username you registered and the API Key provided as your password". STEP 2**: "Set the verification code for this explanatory flow... In the node 'Send Email' set the sender". STEP 3**: "Submit the form and you will receive a call to the phone number you entered where the selected voice will tell you the content of the text you wrote". Set voice code**: "Set the code that will be spoken in the verification phone call". Set email code**: "Set the code that will be sent in the verification email". Required Files 1g8EAij2RwhNN70t_xSend_and_check_TTS_(Text-to-speech)_voice_calls_end_email_verification.json: The n8n workflow export file for this automation. Testing Tips Run the workflow and submit the form with your phone number and email. Check your phone for the voice call and listen for the code. Enter the correct voice code in the next form and submit. Check your email for the second verification code. Enter the correct email code to test the success path, or an incorrect one to test the failure path. Suggested Tags & Categories #Verification #Voice #Email #API #Authentication

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Monetize Your Private LLM Models with x402 and Ollama Self-hosting custom LLMs is becoming more popular and easier with turn-key inferencing tools like Ollama. With Ollama you can host your own proprietary models for customers in a private cloud or on your own hardware. But monetizing custom-trained, propietary models is still a challenge, requiring integrations with payment processors like Stripe, which don't support micropayments for on-demand API consumption. With this free workflow you can quickly monetize your proprietary LLM models with the x402 payment scheme in n8n with 1Shot API. Setup Steps: Authenticate the 1Shot API node against your 1Shot API business account. Point the 1Shot API simulate and execute nodes at the x402-compatible payment token you'd like to receive as payment. Configure the Ollama n8n node in the workflow (with optional authentication) to forward to your Ollama API endpoint and let users query it through an n8n webhook endpoint while paying you directly in your preferred stablecoin (like USDC). Through x402, users and AI agents can pay per-inference, whith no overhead wasted on centralized payment processors. Walkthrough Tutorial Check out the YouTube tutorial for this workflow so see the full end-to-end process.

Short Description: Automatically collect and analyze your competitor’s YouTube performance. This workflow extracts video titles, views, likes, and descriptions from any YouTube channel and saves the data to Google Sheets — helping creators spot viral trends and plan content that performs. Who’s it for For content creators, YouTubers, and marketing teams who want to track what’s working for their competitors — without manually checking their channels every day. How it works This workflow automatically collects data from any YouTube channel you enter. You just write the channel name in the form — n8n fetches the channel ID, gets all recent video IDs, and extracts each video’s title, views, likes, and description. Finally, all the information is saved neatly into a connected Google Sheet for analysis. How to set up Create a Google Sheet with columns for Title, Views, Likes, Description, and URL. Connect your Google account to n8n. Add your YouTube Data API key inside the HTTP Request nodes (use n8n credentials, not hardcoded keys). Update your form submission or trigger node to match your input method. Execute the workflow once to test and verify that data is flowing into your sheet. Requirements YouTube Data API key Google Sheets account n8n cloud or self-hosted instance How to customize You can modify the JavaScript code node to include more metrics (like comments or publish date), filter by keywords, or change the output destination (e.g., Airtable or Notion).

Summarize Gmail Support Emails with Gemini and Post to Slack This workflow automatically checks your Gmail inbox for new support emails, summarizes them using Google Gemini and posts concise summaries directly into Slack. Instead of manually reading long support emails, your team can stay updated with short, actionable insights in real-time. Who’s it for Customer Support Teams** – to stay on top of support tickets without reading lengthy emails. Operations Managers** – who need quick insights on issues raised by customers. Engineering Teams** – who want alerts and summaries of support escalations in Slack. Founders/Execs** – who prefer high-level summaries rather than full email threads. How it works Gmail Trigger – Check Support Emails The workflow runs every minute to detect new incoming emails in your support inbox. Forward Email to Gemini for Summarization Extracts the email body and prepares it for the LLM model. Gemini – Summarize Support Email Google Gemini condenses the email into a short, clear summary. Slack – Post Summary to Channel The summarized text is sent to your chosen Slack channel for instant visibility. How to set up Connect your Gmail account in n8n. Configure the Gmail Trigger to check emails from your support inbox (or apply filters like subject = “Support” or label = “Support”). Add your Google Gemini API credentials in n8n. Configure Gemini with a summarization prompt (e.g., “Summarize this email in 3 bullet points”). Connect your Slack account and select the target channel. Save and activate the workflow. Requirements n8n instance** (self-hosted or cloud). Google Account** with Gmail API enabled. Google Gemini API access** (API key). Slack workspace** with a bot token and permission to post messages. How to customize Change the email filters in the Gmail Trigger (e.g., only unread emails, only with label Support). Modify the summarization style in Gemini (bullet points, short paragraph, etc.). Choose a different Slack channel for posting (e.g., #support, #alerts, #dev-team). Add additional nodes for logging into Google Sheets or creating Jira tickets. Add-ons Save original emails + summaries into Google Sheets for tracking. Create Jira or Trello tasks automatically for high-priority issues. Add a translation step if support emails arrive in multiple languages. Integrate with Zendesk or Freshdesk if you also use those tools. Integrate OpenAI LLM models. Use Case Examples Customer sends a bug report → Gemini summarizes key points → Slack post alerts dev team instantly. Support email with long back-and-forth conversation → condensed into a 3-line summary in Slack. Team lead checks Slack daily instead of logging into Gmail to stay informed. Common Troubleshooting | Issue | Possible Cause | Solution | | -------------------------------- | ------------------------------------- | ---------------------------------------------------------------- | | No emails detected | Gmail Trigger not configured properly | Check Gmail Trigger settings and labels/filters. | | Gemini not summarizing | API key missing or invalid | Re-add Gemini API credentials in n8n. | | Slack not receiving messages | Slack auth expired or wrong channel | Reconnect Slack account and verify channel ID. | | Workflow runs but nothing posted | Summarization output empty | Adjust Gemini prompt or check email format (HTML vs plain text). | 👨‍💻Need help? If you need assistance setting up or customizing this workflow, feel free to reach out WeblineIndia. We can help you: Configure Gmail filters. Optimize Gemini prompts for better summaries. Connect Slack and set up advanced alerts. Extend the workflow with Sheets, Jira or other integrations.