Workflow Templates

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 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.

🎯 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

This workflow creates a Jira issue when a new ticket is created in Zendesk. Subsequent comments on the ticket in Zendesk are added as comments to the issue in Jira. Prerequisites Zendesk account and Zendesk credentials. Jira account and Jira credentials. Jira project to create issues in. How it works The workflow listens for new tickets in Zendesk. When a new ticket is created, the workflow creates a new issue in Jira. The Jira issue key is then saved in one of the ticket's fields (in setup we call this "Jira Issue Key"). The next time a comment is added to the ticket, the workflow retrieves the Jira issue key from the ticket's field and adds the comment to the issue in Jira. Setup This workflow requires that you set up a webhook in Zendesk. To do so, follow the steps below: In the workflow, open the On new Zendesk ticket node and copy the webhook URL. In Zendesk, navigate to Admin Center > Apps and integrations > Webhooks > Actions > Create Webhook. Add all the required details which can be retrieved from the On new Zendesk ticket node. The webhook URL gets added to the “Endpoint URL” field, and the “Request method” should match what is shown in n8n. Save the webhook. In Zendesk, navigate to Admin Center > Objects and rules > Business rules > Triggers > Add trigger. Give the trigger a name such as “New tickets”. Under “Conditions” in “Meet ALL of the following conditions”, add “Status is New”. Under “Actions”, select “Notify active webhook” and select the webhook you created previously. In the JSON body, add the following: { "id": "{{ticket.id}}", "comment": "{{ticket.latest_comment_html}}" } Save the Zendesk trigger. You will also need to set up a field in Zendesk to store the Jira issue key. To do so, follow the steps below: In Zendesk, navigate to Admin Center > Objects and rules > Tickets > Fields > Add field. Use the text field option and give the field a name such as “Jira Issue Key". Save the field. In n8n, open the Update ticket node and select the field you created in Zendesk.

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

Using the knowledge graphs instead of RAG vector stores This workflow creates an AI chatbot agent that has access to several knowledge bases at the same time (used as "experts"). These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows. The advantages of using GraphRAG instead of the standard vector stores for knowledge are: Easy and quick to set up (no complex data import workflows needed) A knowledge graph has a holistic view of your knowledge base Better retrieval of relations between the document chunks = higher quality responses 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. Here's a description step by step: The user submits a question using the AI chatbot (n8n interface, in this case, which can be accessed via a URL or embedded to any website) The AI agent node checks a list of tools it has access to. Each tool has a description of the knowledge it has auto-generated by InfraNodus. The AI agent decides which tool should be used to generate a response. It may reformulate user's query to be more suitable for the expert. The query is then sent to the InfraNodus HTTP node endpoint, which will query the graph that corresponds to that expert. Each InfraNodus GraphRAG expert provides a rich response that takes the whole context into account and provides a response from each expert (graph) along with a list of relevant statements retrieved using a combination or RAG and GraphRAG. The n8n AI Agent node integrates the responses received from the experts to produce the final answer. The final answer is sent back to the user's chat (or a webhook endpoint) How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Create a separate knowledge graph for each expert (using PDF / content import options) in InfraNodus For each graph, go to the workflow, paste the name of the graph into the body name field. Keep other settings intact or learn more about them at the InfraNodus access points page. Once you add one or more graphs as experts to your flow, add the LLM key to the OpenAI node and launch the workflow Requirements An InfraNodus account and API key An OpenAI (or any other LLM) API key Customizing this workflow You can use this same workflow with a Telegram bot, so you can interact with it using Telegram. There are many more customizations available. Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n Also check out the video tutorial with a demo:

🧾 Generate Project Summary from meeting transcript Who’s it for 🤝 Project managers looking to automate client meeting summaries Client success teams needing structured deliverables from transcripts Agencies and consultants who want consistent, repeatable documentation How it works / What it does ⚙️ Trigger: Manual or webhook trigger kicks off the workflow. Get meeting transcript: Reads the raw transcript from a specified Google Docs file. Generate summary: Sends transcript + instructions to OpenAI (gpt-4.1-mini) to produce a structured project summary. Convert to HTML: Transforms the LLM-generated Markdown into styled HTML. Prepare request: Wraps HTML and metadata into a multipart request body. Create Google Doc: Uploads the new “Project Summary” document into your Drive folder. How to set up 🛠️ Credentials Google Docs & Drive OAuth2 credentials OpenAI API key (gpt-4.1-mini) Nodes configuration Manual Trigger / webhook node Google Docs “Get meeting transcript” node: set documentURL AI Chat Model node: select gpt-4.1-mini Markdown node: enable tables & emoji Google Drive “CreateGoogleDoc” node: set target folder ID Paste in your IDs Update documentURL to your transcript doc Update google_drive_folder_id in the Set node Execute Click “Execute Workflow” or call via webhook Requirements 📋 n8n Google OAuth2 scopes for Docs & Drive OpenAI account with GPT-4.1-mini access A Google Drive folder to store summaries How to customize ✨ Output format**: Edit the Markdown prompt in the ChainLlm node to adjust headings or tone Timeline section**: Extend LLM prompt template with your own phase table Styling**: Tweak inline CSS in the Code node (Prepare_Request) for fonts or margins Trigger**: Swap Manual Trigger for HTTP/Webhook trigger to integrate with other tools Language model**: Upgrade to a different model by changing model.value in the AI node

his workflow automates time tracking using location-based triggers. How it works Trigger: It starts when you enter or exit a specified location, triggering a shortcut on your iPhone. Webhook: The shortcut sends a request to a webhook in n8n. Check-In/Check-Out: The webhook receives the request and records the time and whether it was a "Check-In" or "Check-Out" event. Google Sheets: This data is then logged into a Google Sheet, creating a record of your work hours. Set up steps Google Drive: Connect your Google Drive account. Google Sheets: Connect your Google Sheets account. Webhook: Set up a webhook node in n8n. iPhone Shortcuts: Create two shortcuts on your iPhone, one for "Check-In" and one for "Check-Out." Configure Shortcuts: Configure each shortcut to send a request to the webhook with the appropriate "Direction" header. It's easy to setup, around 5 minutes.

Who is this for? NVD (National Vulnerability Database) data is essential for security analysts, vulnerability managers, and DevSecOps professionals who need to perform both CVE lookups and monitor historical change logs. This workflow helps streamline those efforts by providing structured outputs for audit, triage, or compliance tracking purposes. 📝 Note: While this example uses Google Sheets as the destination, you can easily modify the final destination node (e.g., send to Slack, email, database, etc.) based on your specific automation needs.? What problem is this solving? Security teams often manually look up CVE data and track changes across multiple tools. This process is inefficient and error-prone. This workflow automates the CVE lookup and historical change tracking by logging enriched vulnerability data into Google Sheets in real-time. What this workflow does This workflow is designed for CVE API lookup and change history tracking. In many vulnerability automation pipelines, it is essential to determine not only the metadata of a CVE but also how it has evolved over time. Based on the operational need—whether it's enrichment, risk scoring, or remediation validation—this workflow becomes particularly handy in surfacing both current and historical CVE data. This template performs the following actions: Accepts incoming webhook requests containing a CVE ID Queries the NVD CVE Lookup API to fetch vulnerability metadata Queries the NVD CVE History API to retrieve all historical changes Flattens both datasets into a sheet-compatible structure Appends vulnerability metadata to one sheet and change history to another within the same Google Spreadsheet Setup 🔑 Request an NVD API Key To request an NVD API Key, please provide your organization name, a valid email address, and indicate your organization type at NVD API Key Request. You must scroll to the end of the Terms of Use Agreement and check "I agree to the Terms of Use" to obtain an API Key. After submission, you will receive a single-use hyperlink via email to activate and view your API Key. If not activated within seven days, a new request must be submitted. 📊 API Rate Limits Without an API key, you're limited to 5 requests per 30-second window. With an API key, you’re allowed up to 50 requests in the same period. To prevent request throttling, it's recommended to introduce slight delays between consecutive API calls in production setups. Clone or import this workflow into your n8n instance. Set up the following credentials: Google Sheets OAuth2 NVD API Key (via HTTP Header Auth) The workflow logs data to a Google Sheet titled NVD Database, with Sheet 1 named CVE Lookup and Sheet 2 named CVE History. Trigger each workflow using the respective webhook URL, appending ?cveId=CVE-XXXX-XXXX as a query parameter. 🔍 Example Webhook Request (CVE Change History) You can test this workflow with the following example: GET https://your-domain.com/webhook/cve-history?cveId=CVE-2023-34362 How to customize this workflow Use the Edit Fields node (optional) to centralize configuration like sheet name or query input Extend the CVE flattening logic to include more nested metadata if needed Integrate notification systems (e.g., Slack or email) by branching from the processing nodes Modify webhook paths for better endpoint organization 🔐 Production Security Tips Use HTTP Header Auth on the webhook for secure access > ⚠️ This template uses webhooks and NVD API access with authentication headers. This template uses two flows: Webhook 1:** NVD CVE Lookup — Lookup CVE vulnerability metadata from NVD and sync to Google Sheet Webhook 2:** NVD CVE Change History — Track change history for CVEs via NVD and log each update Each flow: Hits NVD’s respective endpoint Uses custom JS Code node to flatten the nested JSON Syncs data to dedicated Google Sheet tabs 🧩 4 nodes: Webhook → API Call → Parse → Sheet Sync Make sure both flows are activated and webhooks exposed for external access. Based on your needs, ensure you have a secure setup—whether hosted internally or in a cloud environment—when running n8n in production.

This workflow analyzes images submitted via a form using OpenAI Vision, then delivers the analysis result directly to your Telegram chat. ✅ Use case examples: • Users submit screenshots for instant AI interpretation • Automated document or receipt analysis with Telegram delivery • Quick OCR or image classification workflows ⸻ ⚙️ Setup Guide Form Submission Trigger • Connect your form app (e.g. Typeform, Tally, or n8n’s own webhook form) to the On form submission trigger node. • Ensure it sends the image file or URL as input. OpenAI Vision Analysis • In the OpenAI node, select Analyze Image operation. • Provide your OpenAI API key and configure the prompt to instruct the model on what to analyze (e.g. “Describe this receipt in detail”). Set Telegram Chat ID • Use this manual node to input your Telegram Chat ID for delivery. • Alternatively, automate this with a database lookup or user session if building for multiple users. Telegram Delivery Node • Connect your Telegram Bot to n8n using your bot token. • Set up the sendMessage operation, using the analysis result from the previous node as the message text. Testing • Click Execute workflow. • Submit an image via your form and confirm it delivers to your Telegram as expected.

Overview This release introduces a Voice-Enabled Tour Recommendation System that leverages n8n, ElevenLabs Voice Agent, OpenAI GPT-4o, and Pinecone Vector DB to deliver personalized travel itineraries based on spoken input. Users speak their preferences to the ElevenLabs voice agent, which then triggers an n8n workflow that returns a tailored tour plan. Features Voice interaction with AI-powered travel agent via ElevenLabs Uses ChatGPT-4o for contextual understanding and generation Dynamic query handling with vector-based search using Pinecone Fast response generation using n8n webhook Modular agent memory and role design for scalable enhancement Pre-requisites n8n account with workflow creation access ElevenLabs account with agent and webhook setup OpenAI API key (GPT-4o access) Pinecone account for vector database A list of vectorized tour packages using this n8n embedder (https://creators.n8n.io/workflows/5085) Setup Instructions Step 1: Configure the Voice Agent Webhook in ElevenLabs Use POST method Webhook URL: https://... Breakdown voice input into: Destination Type of tour Number of days Number of passengers Step 2: Set Up the AI Agent Prompt in ElevenLabs Use a conversational style with summaries, clarifying questions, and affirmations. Example Prompt: “You use a natural speech style and periodically summarize... Your goal is to help callers create a personalized tour plan.” Step 3: Select LLM LLM: GPT-4o Mini Memory window: Up to 5 contexts Step 4: Integrate Tools Use Custom Tool: n8n ID: tool_xxxxxx Tool Description: “Generates travel plan once the details are collected” Step 5: Build n8n Workflow Trigger: Webhook (POST) Process user input: Tour Recommendation AI Agent Use OpenAI Chat Model (GPT-4o) for reasoning Query Pinecone Vector Store using Tour Builder Q&A node Respond with structured Itinerary Plan via webhook response How to use: Execute the n8n workflow (the webhook waits for the voice trigger from elevenlabs) Start the Elevenlabs Voice Agent Request for a tour plan to any destination giving the details of your tour preferences. Wait for the Voice Agent to respond back with tour package suggestions after fetching the tour details from the n8n workflow. Close the conversation. | Area | Improvement | | ------------------ | ----------------------------------------------------- | | 🔉 Voice UX | Natural-sounding travel agent using ElevenLabs | | 💡 Personalization | ChatGPT-4o adapts based on travel style & preferences | | 📚 Knowledge Base | Pinecone-powered vector retrieval of real tour data | | 🔁 Reusability | Modular workflow with reusable embedding tools | | ⚙️ System Design | Separation of memory, logic, and data layers | Who is this for? Travel Agencies & DMCs Offer ultra-personalized packages based on customer queries. Let AI do the matching. Tour Package Aggregators Auto-curate and send matching packages from your catalog — no manual searching needed. Content & Marketing Teams Craft customized tour recommendations for email campaigns and newsletters. Tech-enabled Travel Startups Embed this intelligence in your workflows, CRMs, or chatbots to delight customers.