Workflow Templates

Receive realtime call-event data from telli Purpose and Problem Solved This template automates the process of receiving and acting upon real-time call event data from telli, an AI-powered voice agent platform. It solves the challenge of manually updating CRM records and initiating follow-up actions based on call outcomes. By leveraging webhooks and n8n's powerful workflow capabilities, this template enables businesses to instantly update their Airtable CRM and trigger appropriate follow-up actions, enhancing efficiency and responsiveness in customer interactions. Prerequisites An active telli account with API access and webhook capabilities An Airtable base set up as your CRM n8n instance (cloud or self-hosted) Airtable Specifications Create an Airtable base with the following table and fields: Table: Contacts Fields: Name (Single line text) Phone (Phone number) Email (Email) Appointment_Booked (Checkbox) Interest (Single select: High, Medium, Low) Last_Call_Date (Date) Notes (Long text) Step-by-Step Setup Instructions Webhook Configuration in telli: Log into your telli dashboard Navigate to the webhook settings Set the endpoint URL to your n8n Webhook node URL Select the "call_ended" event to trigger the webhook n8n Workflow Setup: Create a new workflow in n8n Add a Webhook node as the trigger Configure the Webhook node to receive POST requests Parse Webhook Data: Add a Set node to extract relevant information from the webhook payload Map fields such as call_outcome, appointment_booked, and interest Decision Logic: Add a Switch node to create different paths based on the call outcome Create branches for scenarios like "Appointment Booked", "Interested", and "Not Interested" Airtable Integration: Add Airtable nodes for each outcome to update the Contacts table Configure the nodes to update fields like Appointment_Booked, Interest, and Last_Call_Date Follow-up Actions: For "Interested" but not booked outcomes, add an Email node to trigger a follow-up email campaign For "Appointment Booked", add a node to create a calendar event or task Testing and Activation: Use the n8n testing feature to simulate webhook calls and verify each path Once satisfied, activate the workflow Example Workflow Webhook receives a "call_ended" event from telli Set node extracts call_outcome: appointment_booked = true, interest = true Switch node directs to the "Appointment Booked" path Airtable node updates the contact record: Set Appointment_Booked to true Set Interest to "High" Update Last_Call_Date Calendar node creates an appointment for the booked slot Example Payload Below is an example of the payload you might receive from telli when a call ends: { "event": "call_ended", "call": { "call_id": "b4a05730-2abc-4eb0-8066-2e4d23b53ba9", "attempt": 1, "from_number": "+17755719467", "to_number": "+16506794960", "external_contact_id": "external-123", "contact_id": "6bd1e7e0-6d00-4c0b-ad5b-daa72457a27d", "agent_id": "d8931604-92ad-45cf-9071-d9cd2afbad0c", "triggered_at": 1731956924302, "started_at": 1731956932264, "booked_slot_for": "2025-02-24T15:30:00Z", "ended_at": 1731957002078, "call_length_min": 2, "call_status": "COMPLETED", "transcript": "Agent: Hello...", "transcriptObject": [ { "role": "agent", "content": "Hello..." } ], "call_analysis": { "summary": { "value": true, "details": "A call between an agent and a customer talking about buying an ice cream machine" }, "appointment": { "value": true, "details": "2025-02-18T15:30:00Z" }, "interest": { "value": true, "details": "The customer is interested in buying an ice cream machine" } } } } In this example, you can see that the call resulted in a booked appointment and showed customer interest. Your n8n workflow would process this data, updating the Airtable CRM and triggering any necessary follow-up actions. By implementing this template, businesses can automate their post-call processes, ensuring timely follow-ups and accurate CRM updates. This real-time integration between telli's AI voice agents and your Airtable CRM streamlines operations, improves customer engagement, and increases the efficiency of your sales and support teams.

What Does This Flow Do? This workflow demonstrates how to dynamically generate a line chart using the QuickChart node based on data provided in a JSON object and then upload the resulting chart image to Google Drive. Use Cases You can use it in presentations or requesting for chart generation from a software with HTTP requests. Automated report generation (e.g., daily sales charts). Visualizing data fetched from APIs or databases. Simple monitoring dashboards. Adding charts to internal tools or notifications. How it Works Trigger: The workflow starts manually when you click 'Test workflow'. Set Sample Data: A Set node (Edit Fields: Set JSON data to test) defines a sample JSON object named jsonData. This object contains: reportTitle: A title (not used in the chart generation in this example, but useful for context). labels: An array of strings representing the labels for the chart's X-axis (e.g., ["Q1", "Q2", "Q3", "Q4"]). salesData: An array of numbers representing the data points for the chart's Y-axis (e.g., [1250, 1800, 1550, 2100]). Generate Chart: The QuickChart node is configured to: Create a line chart. Dynamically read labels from the jsonData.labels array (Labels Mode: From Array). Use the jsonData.salesData array as the input data (Note: This configuration places data in the top-level 'Data' field. For more complex charts with multiple datasets or specific dataset options, configure datasets under 'Dataset Options' instead). The node outputs the generated chart image as binary data in a field named data. Upload to Google Drive: The Google Drive node (Google Drive: Upload File): Takes the binary data (data) from the QuickChart node. Uploads the image to your specified Google Drive folder. Dynamically names the file based on its extension (e.g., chart.png). Setup Steps Import: Import this template into your n8n instance. Configure Google Drive Credentials: Select the Google Drive: Upload File node. You MUST configure your own Google Drive credentials. Click on the 'Credentials' dropdown and either select existing credentials or create new ones by following the authentication prompts. (Optional) Customize Google Drive Folder: In the Google Drive: Upload File node, you can change the Drive ID and Folder ID to specify exactly where the chart should be uploaded. Activate: Activate the workflow if you want it to run automatically based on a different trigger. How to Use & Customize Change Input Data:** Modify the labels and salesData arrays within the Edit Fields: Set JSON data to test node to use your own data. Ensure the number of labels matches the number of data points. Use Real Data Sources:** Replace the Edit Fields: Set JSON data to test node with nodes that fetch data from real sources like: HTTP Request (APIs) Postgres / MongoDB nodes (Databases) Google Sheets node Ensure the output data from your source node is formatted similarly (providing labels and salesData arrays). You might need another Set node to structure the data correctly before the QuickChart node. Change Chart Type:** In the QuickChart node, modify the Chart Type parameter (e.g., change from line to bar, pie, doughnut, etc.). Customize Chart Appearance:** Explore the Chart Options parameter within the QuickChart node to add titles, change colors, modify axes, etc., using QuickChart's standard JSON configuration options. Use Datasets (Recommended for Complex Charts):** For multiple lines/bars or more control, configure datasets explicitly in the QuickChart node: Remove the expression from the top-level Data field. Go to Dataset Options -> Add option -> Add dataset. Set the Data field within the dataset using an expression like {{ $json.jsonData.salesData }}. You can add multiple datasets this way. Change Output Destination:** Replace the Google Drive: Upload File node with other nodes to handle the chart image differently: Write Binary File: Save the chart to the local filesystem where n8n is running. Slack / Discord / Telegram: Send the chart to messaging platforms. Move Binary Data: Convert the image to Base64 to embed in HTML or return via webhook response. Nodes Used Manual Trigger Set QuickChart Google Drive Tags: (Suggestions for tags field) QuickChart, Chart, Visualization, Line Chart, Google Drive, Reporting, Automation

This n8n workflow demonstrates how to transform natural language date and time expressions into structured data with 96%+ accuracy. Parse complex expressions like "early next July", "2 weeks after project launch", or "end of Q3" into precise datetime objects with confidence scoring, timezone intelligence, and business rules validation for any automation workflow. Good to know Achieves 96%+ accuracy on complex natural language date expressions At time of writing, this is the most advanced open-source date parser available Includes AI learning that improves over time with user corrections Supports 6 languages with auto-detection (English, Spanish, French, German, Italian, Portuguese) Sub-millisecond response times with intelligent caching Enterprise-grade with business intelligence and timezone handling How it works Natural Language Input**: Receives date expressions via webhook, form, email, or chat AI-Powered Parsing**: Your world-class date parser processes the text through: 50+ custom rule patterns for complex expressions Multi-language auto-detection and smart translation Confidence scoring (0.0-1.0) for AI decision-making Ambiguity detection with helpful suggestions Business Intelligence**: Applies enterprise rules automatically: Holiday calendar awareness (US + International) Working hours validation and warnings Business day auto-adjustment Timezone normalization (IANA format) Smart Scheduling**: Creates calendar events with: Structured datetime objects (start/end times) Confidence metadata for workflow decisions Alternative interpretations for ambiguous inputs Rich context for follow-up actions Integration Ready**: Outputs connect seamlessly to: Google Calendar, Outlook, Apple Calendar CRM systems (HubSpot, Salesforce) Project management tools (Notion, Asana) Communication platforms (Slack, Teams) How to use The webhook trigger receives natural language date requests from any source Replace the MCP server URL with your deployed date parser endpoint Configure timezone preferences for your organization Customize business rules (working hours, holidays) in the parser settings Connect calendar integration nodes for automatic event creation Add notification workflows for scheduling confirmations Use Cases Meeting Scheduling**: "Schedule our quarterly review for early Q3" Project Management**: "Set deadline 2 weeks after product launch" Event Planning**: "Book venue for the weekend before Labor Day" Personal Assistant**: "Remind me about dentist appointment next Tuesday morning" International Teams**: "Team standup tomorrow morning" (auto-timezone conversion) Seasonal Planning**: "Launch campaign in late spring 2025" Requirements Natural Language Date Parser MCP server (provided code) Webhook endpoint or form trigger Calendar integration (Google Calendar, Outlook, etc.) Optional: Slack/Teams for notifications Optional: Database for learning pattern storage Customizing this workflow Multi-language Support**: Enable auto-detection for global teams Business Rules**: Configure company holidays and working hours Learning System**: Enable AI learning from user corrections Integration Depth**: Connect to your existing calendar and CRM systems Confidence Thresholds**: Set minimum confidence levels for auto-scheduling Ambiguity Handling**: Route unclear dates to human review or clarification requests Sample Input/Output Input Examples: "early next July" "2 weeks after Thanksgiving" "next Wednesday evening" "Q3 2025" "mañana por la mañana" (Spanish) "first thing Monday" Rich Output: { "parsed": [{ "start": "2025-07-01T00:00:00Z", "end": "2025-07-10T23:59:59Z", "timezone": "America/New_York" }], "confidence": 0.95, "method": "custom_rules", "business_insights": [{ "type": "business_warning", "message": "Selected date range includes July 4th holiday" }], "predictions": [{ "type": "time_preference", "suggestion": "You usually schedule meetings at 10 AM" }], "ambiguities": [], "alternatives": [{ "interpretation": "Early July 2026", "confidence": 0.15 }], "performance": { "cache_hit": true, "response_time": "0.8ms" } } Why This Workflow is Unique World-Class Accuracy**: 96%+ success rate on complex expressions AI Learning**: Improves over time with user feedback Global Ready**: Multi-language and timezone intelligence Business Smart**: Enterprise rules and holiday awareness Performance Optimized**: Sub-millisecond cached responses Context Aware**: Provides confidence scores and alternatives for AI decision-making Transform your scheduling workflows from rigid form inputs to natural, conversational date requests that your users will love!

🎯 What It Does: This project lets you talk to Siri (via Apple Shortcuts) and record or query your daily spending. The shortcut sends your message to an n8n Webhook, which uses AI to decide whether it’s for writing or reading finance data, then replies with a human-friendly message — all powered by n8n + AI + Google Sheets. ⸻ 🌐 PART 1: n8n Setup 🧩 1. Create a Webhook Trigger in n8n • Add a node: Webhook • Set HTTP Method: POST • Set Path: siri-finance • Enable “Respond to Webhook” = ✅ 🧠 2. Add AI Agent Node (e.g. OpenAI, Ollama, Gemini) • Use system prompt like: You are a finance assistant. Decide if the user wants to record or read transactions. If it's recording, return a JSON object with date, type, name, amount, and expense/income. If it's reading, return date range and type (Expense/Income). Always reply with a human-friendly summary. • Input: {{ $json.text }} (from webhook) • Output: structured json.output 🧮 3. (Optional) Add Logic to write to DB / Supabase / Google Sheets • Append tool: Adds a new row • Read tool: Queries past data Now your n8n flow is ready! ⸻ 📱 PART 2: iOS Shortcut Setup ⚙️ 1. Create a new Shortcut • Name it: 記帳助理 (or Finance Bot) • Add Action: Ask for Input • Prompt: “請說出你的記帳內容” • Input Type: Text • Add Action: Get Contents of URL • Method: POST • URL: https://your-n8n-domain/webhook/siri-finance • Headers: Content-Type: application/json • Request Body: { "text": "Provided Input" } • Replace "Provided Input" with Magic Variable → Input Result 🔊 2. Show Result • Add Action: Show Result • Content: Get Contents of URL 🗣️ 3. Optional: Add “Speak Text” • If you want Siri to speak it back, add Speak Text after Show Result. ⸻ ✅ Example Usage • You: “Hey Siri, 開支$50 早餐” • Siri: “已記錄支出：項目 早餐，金額 $50，已寫入” Or • You: “查一下我過去7日用了幾多錢” • Siri: “你過去7日總支出為 $7684.64，包括：⋯⋯” ⸻ 📦 Files to Share You can package the following: • .shortcut file export • Sample n8n workflow .json • Optional Supabase schema / Google Sheet template ⸻ 💡 Tips for Newcomers • Keep your Webhook public but protect with token if needed. • Ensure you handle emoji and newline safely for iOS compatibility. • Add logging nodes in n8n to help debug Siri messages. ⸻ 🗣️ Optional Project Name “Siri 記帳助理” / “Finance VoiceBot” A simple voice-first way to manage your daily expenses.

❓ What Problem Does It Solve? Manual exporting or copying of leads and newsletter signups from web forms to spreadsheets is time-consuming, error-prone, and delays follow-ups or marketing activities. Traditional workflows can lose data due to mistakes or lack of automation. The Fluentform Export workflow automates the capture and organization of form submissions and newsletter signups into Google Sheets 💡 Why Use this workflow? Save Time:** Automate tedious manual data entry for form leads and newsletter signups Avoid Data Loss:** Ensure all submissions are reliably logged with real-time updates Organized Data:** Separate sheets for newsletter and contact form data maintain clarity Easy Integration:** Works seamlessly with Fluentform submissions and Google Sheets Flexible & Scalable:** Quickly adapt to changes in form structure or spreadsheet columns ⚡ Who Is This For? Marketers & Growth Teams:** Automatically gather leads and newsletter contacts to fuel campaigns Small to Medium Businesses:** Reduce overhead from manual data management and errors Customer Support Teams:** Keep track of form submissions in a centralized, accessible place Website Admins:** Simplify data workflow from Fluentform plugins without coding 🔧 What This Workflow Does ⏱ Trigger:** Listens for incoming POST requests from Fluentform via webhook 📎 Step 2:** Evaluates if the submission is a newsletter signup or a form based on a specific token 🔄 Step 3 (Newsletter Path):** Maps email from newsletter submissions and appends/updates Google Sheets "News Letter" tab 🔄 Step 3 (Form Path):** Extracts full name, email, phone, subject, and message fields and appends/updates the Google Sheets "form" tab 💌 Step 4:** Sends a JSON success response back to Fluentform confirming receipt 🔐 Setup Instructions Import the provided .json workflow file into your n8n instance Set up credentials: Google Sheets OAuth2 credential with access to your target spreadsheets Customize workflow elements: Update Fluentform webhook URL in your Fluentform settings to the n8n webhook URL generated Adjust field names or spreadsheet columns if your form structure changes Update spreadsheet IDs and sheet names used in the Google Sheets nodes to match your own Sheets Test workflow thoroughly with actual Fluentform submissions to verify data flows correctly 🧩 Pre-Requirements Running n8n instance (Cloud or self-hosted) Google account with access to Google Sheets and OAuth credentials Fluentform installed on your website with ability to set webhook URL Target Google Sheets prepared with tabs named "News Letter" and "form" with expected columns 🧠 Nodes Used Webhook (POST - Retrieve Leads) If (Form or newsletter?) Set (newsletter and form data preparation) Google Sheets (Append/update for newsletter and form sheets) Respond to Webhook 📞 Support Made by: khaisa Studio Tag: automation, Google Sheets, Fluentform, Leads Category: Marketing Need a custom? Contact Me

How it works Trigger: Listens for an incoming chat message Copy Assistant: Feeds the message (plus memory) into an OpenAI Chat Model and exposes two “tools” Cold Email Writer Tool Sales Letter Tool• Tool execution: Depending on the user’s intent, the appropriate tool generates the copy • Save output: Writes the generated email or sales letter into your target document via the Update a document node Set up steps • Configure your OpenAI Chat Model credentials in n8n (no hard-coded keys!) • Add and authenticate the Simple Memory credential (to keep context across messages) • Create Google Docs (or MS Word) credentials for the Update a document node • Ensure your Chat trigger is pointing at your incoming-message endpoint • Mandatory: Drop sticky-note annotations on each tool node explaining where to enter API keys and how to tweak prompts Once everything’s wired up, send a test chat message like “Write me a cold email for a fintech startup” and watch the workflow spin up a polished draft in your document. How to use Import the workflow JSON into n8n. Configure your Chat trigger (webhook or form) to receive incoming messages. Send a chat prompt like: “Write me a cold email for a B2B SaaS offering.” The “Copy Assistant” custom GPT picks the right tool (Cold Email or Sales Letter). Generated copy is written directly into your linked Google Doc or Word document. Requirements OpenAI API Key (with Chat Completions & Custom GPTs enabled) Custom Assistant created in your ChatGPT dashboard (Assistant ID pasted into the Chat Model node) n8n instance (Cloud or self-hosted) with credentials set up for: Simple Memory (to persist context) Google Docs or Microsoft Word (for document output) Customising this workflow Tweak system and user prompts inside the Copy Assistant node to fit your brand voice. Swap in Slack, Teams or email nodes instead of a document writer to deliver copy where you need it. Add or remove tools (e.g., “Follow-up Email Writer”) by duplicating the existing tool pattern. Use sticky-note annotations on every node to explain where to enter API keys, Assistant IDs, or prompt tweaks.

How it works This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt. How to use Create an account and apply for an API key on https://ai.nero.com/ai-api?utm_source=n8n-base-workflow. Fill your key into the Create task and Query task status nodes. Select an AI service and modify Create task node parameters, the API doc: https://ai.nero.com/ai-api/docs. Execute the workflow so that the webhook starts listening. Make a test request by postman or other tools, the test URL from the Webhook node. You will receive the output in the webhook response. Our API doc Please create an account to access our API docs. https://ai.nero.com/ai-api/docs. Use cases Large Scale Printing Upscale images into ultra-sharp, billboard-ready masterpieces with 300+ DPI and billions of pixels. Game Assets Compression Improve your game performance with AI-Image Compression: Faster, Better & Lossless. E-commerce Image Editing Remove & replace your product image backgrounds, create virtual showrooms. Photo Retouching Remove & reduce grains & noises from images. Face Animation Transform static images into dynamic facial expression videos or GIFs with our cutting-edge Face Animation API Photo Restoration Our Al-driven Photo Restoration API offers advanced scratch removal, face enhancement, and image upscaling. Colorize Photo Transform black & white images into vivid colors. Avatar Generator Turn your selfie into custom avatars with different styles and backgrounds Website Compression Speed up your website, compress your images in bulk.

Template Description This n8n workflow template allows you to create a masked email address using the Fastmail API, triggered by a webhook. This is especially useful for generating disposable email addresses for privacy-conscious users or for testing purposes. Workflow Details: Webhook Trigger: The workflow is initiated by sending a POST request to a specific webhook. You can include state and description in your request body to customize the masked email's state and description. Session Retrieval: The workflow makes an HTTP request to the Fastmail API to retrieve session information. It uses this data to authenticate further requests. Create Masked Email: Using the retrieved session data, the workflow sends a POST request to Fastmail's JMAP API to create a masked email. It uses the provided state and description from the webhook payload. Prepare Output: Once the masked email is successfully created, the workflow extracts the email address and attaches the description for further processing. Respond to Webhook: Finally, the workflow responds to the original POST request with the newly created masked email and its description. Requirements: Fastmail API Access**: You will need valid API credentials for Fastmail configured with HTTP Header Authentication. Authorization Setup**: Optionally set up authorization if your webhook is exposed to the internet to prevent misuse. Custom Webhook Request**: Use a tool like curl or create a shortcut on macOS/iOS to send the POST request to the webhook with the necessary JSON payload, like so: curl -X POST -H 'Content-Type: application/json' https://your-n8n-instance/webhook/87f9abd1-2c9b-4d1f-8c7f-2261f4698c3c -d '{"state": "pending", "description": "my mega fancy masked email"}' This template simplifies the process of integrating masked email functionality into your projects or workflows and can be extended for various use cases. Feel free to use the companion shortcut I've also created. Please update the authorization header in the shortcut if needed. https://www.icloud.com/shortcuts/ac249b50eab34c04acd9fb522f9f7068

Who is this template for? This template is designed for developers, DevOps engineers, and automation enthusiasts who want to streamline their GitLab merge request process using n8n, a low-code workflow automation tool. It eliminates manual intervention by automating the merging of GitLab branches through API calls. How it works ? Trigger the workflow: The workflow can be triggered by a webhook, a scheduled event, or a GitLab event (e.g., a new merge request is created or approved). Fetch Merge Request Details: n8n makes an API call to GitLab to retrieve merge request details. Check Merge Conditions: The workflow validates whether the merge request meets predefined conditions (e.g., approvals met, CI/CD pipelines passed). Perform the Merge: If all conditions are met, n8n sends a request to the GitLab API to merge the branch automatically. Setup Steps 1. Prerequisites An n8n instance (Self-hosted or Cloud) A GitLab personal access token with API access A GitLab repository with merge requests enabled 2. Create the n8n Workflow Set up a trigger: Choose a trigger node (Webhook, Cron, or GitLab Trigger). Fetch merge request details: Add an HTTP Request node to call GET /merge_requests/:id from GitLab API. Validate conditions: Check if the merge request has necessary approvals. Ensure CI/CD pipelines have passed. Merge the request: Use an HTTP Request node to call PUT /merge_requests/:id/merge API. 3. Test the Workflow Create a test merge request. Check if the workflow triggers and merges automatically. Debug using n8n logs if needed. 4. Deploy and Monitor Deploy the workflow in production. Use n8n’s monitoring features to track execution. This template enables seamless GitLab merge automation, improving efficiency and reducing manual work! Note: Never hard code API token or secret in your https request.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Description This workflow automates document processing and structured table extraction using the Nanonets API. You can submit a PDF file via an n8n form trigger or webhook—the workflow then forwards the document to Nanonets, waits for asynchronous parsing to finish, retrieves the results (including header fields and line items/tables), and returns the output as an Excel file. Ideal for automating invoice, receipt, or order data extraction with downstream business use. How It Works A document is uploaded (via n8n form or webhook). The PDF is sent to the Nanonets Workflow API for parsing. The workflow waits until processing is complete. Parsed results are fetched. Both top-level fields and any table rows/line items are extracted and restructured. Data is exported to Excel format and delivered to the requester. Setup Steps Nanonets Account: Register for a Nanonets account and set up a workflow for your specific document type (e.g., invoice, receipt). Credentials in n8n: Add HTTP Basic Auth credentials in n8n for the Nanonets API (never store credentials directly in node parameters). Webhook/Form Configuration: Option 1: Configure and enable the included n8n Form Trigger node for document uploads. Option 2: Use the included Webhook node to accept external POSTs with a PDF file. Adjust Workflow: Update any HTTP nodes to use your credential profile. Insert your Nanonets Workflow ID in all relevant nodes. Test the Workflow: Enable the workflow and try with a sample document. Features Accepts documents via n8n Form Trigger or direct webhook POST. Securely sends files to Nanonets for document parsing (credentials stored in n8n credentials manager). Automatically waits for async processing, checking Nanonets until results are ready. Extracts both header data and all table/line items into a tabular format. Exports results as an Excel file download. Modular nodes allow easy customization or extension. Prerequisites Nanonets account** with workflow configured for your document type. n8n** instance with HTTP Request, Webhook/Form, Code, and Excel/Spreadsheet nodes enabled. Valid HTTP Basic Auth credentials** saved in n8n for API access. Example Use Cases | Scenario | Benefit | |-----------------------|--------------------------------------------------| | Invoice Processing | Automated extraction of line items and totals | | Receipt Digitization | Parse amounts and charges for expense reports | | Purchase Orders | Convert scanned POs into structured Excel sheets | Notes You must set up credentials in the n8n credentials manager—do not store API keys directly in nodes. All configuration and endpoints are clearly explained with inline sticky notes in the workflow editor. Easily adaptable for other document types or similar APIs—just modify endpoints and result mapping.

Who this is for? Extract Amazon Best Seller Electronic Info is an automated workflow that extracts best seller data from Amazon's Electronics section using Bright Data Web Unlocker, transform it into structured JSON using Google Gemini's LLM, and forwards a fully structured JSON response to a specified webhook for downstream use. This workflow is tailored for: eCommerce Analysts** Who need to monitor Amazon best-seller trends in the Electronics category and track changes in real-time or on a schedule. Product Intelligence Teams** Who want structured insights on competitor offerings, including rankings, prices, ratings, and promotions. AI-powered Chatbot Developers** Who are building assistants capable of answering product-related queries with fresh, structured data from Amazon. Growth Hackers & Marketers** Looking to automate competitive research and surface trending product data to inform pricing strategies. Data Aggregators and Price Trackers** Who need reliable and smart scraping of Amazon data enriched with AI-driven parsing. What problem is this workflow solving? Keeping up with Amazon's best sellers in Electronics is a time-consuming, error-prone task when done manually.This workflow automates the process, ensuring:​ Automating Data Extraction from Amazon Best Sellers using Bright Data, ensuring reliable access to real-time, structured data. Enhancing Raw Data with Google Gemini, turning product lists into structured JSON using the Google Gemini LLM. Sending Results to a Webhook, enabling seamless integration into dashboards, databases, or chatbots. What this workflow does The workflow performs the following steps:​ Extracts Amazon Best Seller Electronics page info using Bright Data's Web Unlocker API. Processes the unstructured content using Google Gemini's Flash Exp model to extract structured product data. Sends the structured information to a webhook endpoint. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Amazon URL with the Bright Data zone by navigating to the Amazon URL with the Bright Data Zone node. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a market researcher, e-commerce entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Change the Amazon Category** Update the Amazon URL with the topic of your interest such as Computers & Accessories, Home Audio, etc. Customize the Gemini Prompt** Update the Gemini prompt to get different styles of output — comparison tables, summaries, feature highlights, etc. Send Output to Other Destinations** Replace the Webhook URL to forward output to: Google Sheets Airtable Slack or Discord Custom API endpoints

This workflow is designed for e-commerce store owners, operations managers, and developers who use Shopify as their e-commerce platform and want an automated way to track and analyze their order data. It is particularly useful for businesses that: Need a centralized view of all Shopify orders Want to analyze order trends without logging into Shopify Need to share order data with team members who don't have Shopify access Want to build custom reports based on order information What Problem Is This Workflow Solving? While Shopify provides excellent order management within its platform, many businesses need their order data available in other systems for various purposes: Data accessibility**: Not everyone in your organization may have access to Shopify's admin interface Custom reporting**: Google Sheets allows for flexible analysis and report creation Data integration**: Having orders in Google Sheets makes it easier to combine with other business data Backup**: Creates an additional backup of your critical order information What This Workflow Does This n8n workflow creates an automated bridge between your Shopify store and Google Sheets: Listens for new order notifications from your Shopify store via webhooks Processes the incoming order data and transforms it into a structured format Stores each new order in a dedicated Google Sheets spreadsheet Sends real-time notifications to Telegram when new orders are received or errors occur Setup Create a Google Sheet Create a new Google Sheet to store your orders Add a sheet named "orders" with the following columns: orderId orderNumber created_at processed processed_at json customer shippingAddress lineItems totalPrice currency Set Up Telegram Bot Create a Telegram bot using BotFather (send /newbot to @BotFather) Save your bot token for use in n8n credentials Start a chat with your bot and get your chat ID (you can use @userinfobot) Configure the Workflow Set your Google Sheet ID in the "Edit Variables" node Enter your Telegram chat ID in the "Edit Variables" node Set up your Telegram API credentials in n8n Configure Shopify Webhook In your Shopify admin, go to: Settings > Notifications > Webhooks Create a new webhook for "Order creation" Set the URL to your n8n webhook URL (from the "Receive New Shopify Order" node) Set the format to JSON How to Customize This Workflow to Your Needs Additional data**: Modify the "Transform Order Data to Standard Format" function to extract more Shopify data Multiple sheets**: Duplicate the Google Sheets node to store different aspects of orders in separate sheets Telegram messages**: Customize the text in Telegram nodes to include more details or rich formatting Data processing**: Add nodes to perform calculations or transformations on order data Additional notifications**: Add more channels like Slack, Discord, or SMS Integrations**: Extend the workflow to send order data to other systems like CRMs, ERPs, or accounting software Final Notes This workflow serves as a foundation that you can build upon to create a comprehensive order management system tailored to your specific business needs.