Workflow Templates

SmartSupport Flow: Auto-Handle IT Requests from Email to JIRA with Slack notification Watch the demo video below: Who’s it for > This workflow is built for lean IT teams, office managers, and business operators who receive support requests via email and want to automate ticket creation, smart AI resolution advice, and seamless communication with both users and internal teams, all without lifting a finger. If your team is tired of manually triaging inbox requests, this AI-powered flow will transform your support handling process. How it works / What it does Trigger on New Email: Uses Gmail Trigger to detect new support request emails. Fetch Email Content: Retrieves the full message body and metadata. Check for Duplication: Skips processing if the email has already been handled (based on READ/UNREAD label). Mark as Read: Updates Gmail to mark the email as processed. Extract Structured Request: Uses the Support Request Reader Agent powered by OpenAI to extract: Request title Request description Requested by Department Category and priority Create Jira Ticket: A main issue is created in Jira using the structured request. Generate AI-Based Solution: Invokes the IT Support Advisor Agent to propose resolution(s). Post Comment to Jira: Adds the suggested solution(s) to the issue as a comment. Notify IT Team: Sends the ticket and context to a Slack channel for visibility and action. (Optional) Send Email to Requester: Currently deactivated. Can be enabled to acknowledge receipt. How to set up Gmail Integration Connect Gmail in the “Gmail Trigger” and “Get Email Content” nodes. OpenAI Configuration Use OpenAI API credentials in both the Reader and Advisor agent models. Jira Integration Authenticate your Jira account. Set project key and issue fields in the “Create Main Issue” node. Slack Notification Configure Slack connection and select a target channel. Set up Jira, Slack, Email Set your company Jira based URL, IT Support slack channel and IT Support email in the Edit Fields (Set) node (Optional) Email Acknowledgment Provide SendGrid credentials and email template in the “Send email to requester” node if re-enabled. Requirements Gmail API access with appropriate permissions OpenAI account with API access (for GPT-4 or GPT-3.5) Jira instance with project and permission to create/comment on issues Slack workspace and Webhook or OAuth setup n8n instance running with all above integrations configured How to customize the workflow Enhance Email Deduplication**: Adjust the deduplication logic to use message-id, threadId, or custom headers. Expand Reader Agent**: Configure the LLM to extract more details such as asset tags, urgency levels, or locations. Tailor Advisor Agent**: Adjust prompt to generate multiple solutions, troubleshooting guides, or internal references. Routing by Department**: Add logic to forward requests to different teams based on the request category or department. Enable Email Acknowledgment**: Activate and customize the email notification step to inform requesters that their issue is being handled.

One-Line Description Automatically detects missed Zoom demos booked via Calendly and triggers AI-powered follow-up sequences. Detailed Description What it does: When a prospect books a demo through Calendly but fails to join the Zoom meeting, this workflow automatically detects the no-show, generates personalized recovery messages using AI, updates your database, and notifies your sales team—all within minutes of the meeting ending. It bridges Calendly, Zoom, and your follow-up channels to ensure no lead falls through the cracks. Who it's for: Sales teams** running high-volume demo calendars who lose 20-40% of booked meetings to no-shows Customer success managers** conducting onboarding calls where attendance tracking matters SDRs and BDRs** who need immediate alerts when prospects miss scheduled meetings Revenue operations teams** seeking to improve demo-to-opportunity conversion rates through faster follow-up Key Features: Real-time no-show detection** - Automatically checks Zoom participant lists against expected attendees within seconds of meeting end AI-generated recovery messaging** - Creates contextual, empathetic follow-up emails and LinkedIn messages tailored to each no-show scenario Instant team notifications** - Sends formatted Slack alerts with attendee details and suggested next actions so reps can manually follow up if needed Attendance tracking database** - Maintains a searchable record of all bookings and attendance status for reporting and analysis Multi-channel follow-up orchestration** - Coordinates email, Slack notifications, and optional CRM updates from a single automation Selective event filtering** - Processes only specific Calendly event types so you control which meetings trigger the workflow How it works: Booking capture: Calendly webhook fires when a demo is scheduled, extracting Zoom meeting details and attendee information Meeting monitoring: When the Zoom meeting ends, a second webhook triggers attendance verification by pulling the participant list from Zoom's API No-show identification: Workflow cross-references the expected attendee email with actual Zoom participants to confirm whether they attended Automated response: For confirmed no-shows, AI generates personalized recovery messages while the system updates your database and notifies your team via Slack Optional integrations: Simultaneously updates CRM deal stages or triggers additional follow-up sequences based on your configuration Setup Requirements Prerequisites: Calendly account** (any paid plan) with webhook access and Personal Access Token Zoom account** (Pro or higher) with Server-to-Server OAuth app credentials for API access OpenAI API key** for AI-generated follow-up message creation Slack workspace** with OAuth permissions to post messages (optional but recommended) n8n Data Table** created with columns: meeting_id, email, status (built-in n8n feature, no external database needed) Email sending service** configured in n8n (SMTP, Gmail, SendGrid, etc.) if enabling automated email sending CRM API access** (HubSpot, Salesforce, Pipedrive, etc.) if enabling deal updates (optional) Note: Zoom API has rate limits (varies by plan); this workflow makes 1-2 API calls per meeting end event. Estimated Setup Time: 45-60 minutes including Zoom app creation, Calendly webhook configuration, and Data Table setup Installation Notes Critical setup steps: Zoom webhook validation**: You must complete Zoom's webhook endpoint validation process before receiving real events. The workflow includes a dedicated validation path—run it once after creating your Zoom app. Calendly webhook creation**: Use the "Manual Setup Trigger" path in the workflow to programmatically create your Calendly webhook subscription. This only needs to run once. Event type filtering**: Replace the placeholder YOUR_CALENDLY_EVENT_TYPE_URI with your specific demo event type URI from Calendly to avoid processing all meeting types. Test with a real meeting**: Book a test demo, join briefly with a different email than the booking email, then leave. The workflow should detect the "no-show" for the booking email. Common pitfalls to avoid: Forgetting to enable the disabled "Send Recovery Email" node after testing (it's disabled by default to prevent accidental sends during setup) Not configuring Zoom Server-to-Server OAuth correctly (requires Account ID, Client ID, and Client Secret—not JWT credentials) Using a personal Calendly account instead of an organization account (webhooks require organization-level access) Overlooking the Data Table creation step—the workflow will fail without this internal database Testing recommendations: Start with Slack notifications only (leave email sending disabled) to verify the workflow logic Use your own email as a test booking to safely generate AI messages without sending to real prospects Check the Data Table after each test to confirm booking records are being created and updated correctly Customization Options Easy modifications: Swap email for SMS**: Replace the email node with Twilio SMS to send text message follow-ups instead Add delays**: Insert "Wait" nodes to schedule follow-ups hours or days later rather than immediately Change AI tone**: Modify the OpenAI prompt to match your brand voice (casual, formal, humorous, etc.) Multi-step sequences**: Duplicate the AI and email nodes to create a 3-touch follow-up cadence over several days Different CRM platforms**: The HubSpot node can be swapped for Salesforce, Pipedrive, or any CRM n8n supports Extension possibilities: Add Google Sheets logging for executive dashboard reporting on no-show rates Integrate with Calendly's rescheduling API to automatically send rebooking links Connect to Loom or Vidyard APIs to attach pre-recorded demo videos in follow-up emails Create a "second chance" discount workflow that offers incentives for rescheduling Build a predictive model by exporting no-show data to analyze patterns (time of day, lead source, etc.) Category Sales Tags calendly zoom no-show-recovery demo-automation lead-follow-up sales-automation meeting-tracking ai-messaging slack-notification openai Use Case Examples SaaS sales team**: A B2B software company runs 40+ demos per week. When prospects no-show, this workflow immediately notifies the assigned rep in Slack with a pre-written LinkedIn message, sends an empathetic recovery email offering a Loom recording alternative, and flags the deal in HubSpot for manual outreach within 2 hours. Agency onboarding**: A marketing agency conducts discovery calls with new clients. If a client misses their scheduled kickoff meeting, the workflow logs the no-show, updates the client status in their CRM, and sends a friendly rescheduling email with three alternative time slots—all before the account manager even notices. Customer success**: A customer onboarding team tracks training session attendance. When users don't join their scheduled implementation calls, the workflow automatically sends a resource-rich email with documentation links, notifies the CSM team channel, and schedules a follow-up task in their project management tool.

Who's it for This workflow is perfect for individuals, small businesses, or households who need to: Automatically process and categorize expense receipts Extract structured data from invoices and receipts using AI Store receipts in multiple locations (Google Drive and S3) Send automated email notifications with expense details Send documents to accounting systems via email hooks How it works This comprehensive expense processing workflow combines AI-powered document analysis with automated file management and notifications. Here's the complete flow: Form Submission: Users submit expenses through a web form with receipt upload and category selection (Personal, Business, or Shared/Home) AI Document Processing: The workflow extracts text from PDF receipts using OCR, then uses Google Gemini AI to parse and structure the data into a standardized JSON format including vendor details, amounts, dates, and categorization Smart Routing: Based on the expense category, receipts are automatically routed to different processing paths with category-specific folder organization Multi-Destination Storage: Receipts are uploaded to: Google Drive (organized by year/month folders) S3 cloud storage buckets Different destinations based on expense type Email Notifications: Sends formatted HTML email notifications with complete expense details and links to stored receipts Accounting System Integration: Automatically forwards business expenses to accounting systems via email hooks (customizable per user requirements) Requirements Credentials needed: Google Gemini API**: For AI-powered document analysis Google Drive OAuth2**: For personal and business drive access Gmail OAuth2**: For sending email notifications S3 Storage**: For cloud backup (AWS S3, Wasabi, etc.) Services used: Google Drive (multiple accounts supported) Google Gemini AI Gmail S3-compatible storage Form trigger webhook How to set up Step 1: Configure Credentials Set up Google Gemini API credentials in n8n Configure Google Drive OAuth2 for both personal and business accounts Add Gmail OAuth2 credentials Set up S3 storage credentials Step 2: Update Configuration Replace all placeholder values: YOUR_GEMINI_CREDENTIAL_ID with your Gemini credential ID YOUR_PERSONAL_GDRIVE_CREDENTIAL_ID with personal Drive credential YOUR_BUSINESS_GDRIVE_CREDENTIAL_ID with business Drive credential YOUR_GMAIL_CREDENTIAL_ID with Gmail credential YOUR_S3_CREDENTIAL_ID with S3 credential Update Google Drive folder structure: Replace YOUR_BUSINESS_DRIVE_ID and YOUR_SHARED_DRIVE_ID with actual drive IDs Update the JavaScript code in the three Code nodes with your actual folder mapping Configure email addresses: Replace user@example.com with your notification email Replace receipts@paperless-service.com with your accounting system's email hook (this is a mail hook for uploading documents to small business accounting systems - can be modified per user requirements) Update S3 bucket names: Replace business-expenses, personal-expenses, and shared-expenses with your bucket names Step 3: Set Up Folder Structure Create organized folder structures in your Google Drives: Drive Root/ ├── 2024/ │ ├── January/ │ ├── February/ │ └── ... (all months) ├── 2025/ │ ├── January/ │ └── ... (all months) └── 2026/ └── ... (all months) Step 4: Test the Workflow Activate the workflow Submit a test expense through the form Verify files are uploaded to correct locations Check email notifications are received How to customize the workflow Expense Categories Modify the form dropdown options and conditional logic to add/remove expense categories: Edit the "On form submission" node form fields Update the IF condition nodes for routing Add new processing paths as needed AI Processing Schema Customize the structured output parser schema to extract different fields: Modify the JSON schema in the "Structured Output Parser" node Update the AI system prompt for different extraction requirements Add new fields for specific business needs Storage Destinations Add or modify storage locations: Duplicate upload nodes for additional cloud services Modify folder organization logic in Code nodes Add new conditional routing for different storage rules Email Templates Customize the HTML email template: Edit the email message content in the Gmail node Add/remove expense fields in the table Modify styling and branding Folder Organization Update the JavaScript code in Code nodes to match your folder structure: Modify the CSV data with your actual folder IDs Change the date-based organization logic Add custom folder naming conventions Integration Extensions Extend the workflow with additional integrations: Add Slack notifications Connect to accounting software (QuickBooks, Xero) Integrate with expense management platforms Add approval workflows for business expenses

This n8n template demonstrates how to use AI to fully automate the generation and scheduling of X (formerly Twitter) content based on a specific, predefined persona. Use cases are many: It's perfect for social media marketers looking to streamline content creation, individual experts building a consistent brand voice, or businesses aiming to drive traffic to specific services with a steady stream of relevant content. Good to know The AI model used in this workflow (via OpenRouter) requires an API key and will incur costs based on usage (typically a few cents per generation). The Blotato node used for posting is a third-party community node and requires a separate Blotato account. How it works This workflow is divided into two main processes: Content Generation and Content Posting. Content Generation Process: A Schedule Trigger kicks off the workflow every 4 hours. An AI Agent (LangChain) generates a post based on a detailed prompt defining a persona, purpose, and rules. A Code node refines the AI's output, ensuring the text ends naturally. The generated post is then saved to a Google Sheet with a "Not Posted" status, creating a content queue. Content Posting Process: The workflow retrieves one "Not Posted" item from the Google Sheet. An IF node checks the post's category to determine if an image is required. If an image is needed, it searches for and retrieves a matching image file from a specified Google Drive folder. The Blotato node posts the text (and image, if applicable) to the designated X (Twitter) account. A confirmation email is sent via Gmail to notify stakeholders of the successful post. Finally, the Google Sheet status is updated to "Completed" to prevent duplicate posts. How to use You can test the workflow anytime using the manual trigger. For production, adjust the posting frequency in the "Trigger: Every 4 Hours" node. The quality of the generated content is determined by the prompt. Edit the system message within the "AI: Generate X Post Content" node to customize the persona, purpose, tone of voice, etc. To generate posts with images, you must upload image files to the specified Google Drive folder. The filename must exactly match the post's category name (e.g., Evidence-based_Graph.png). Requirements An OpenRouter account (or another AI service account) for the LLM. A Blotato account for social media posting. A Google account for content management, image storage, and notifications (Sheets, Drive, Gmail). Customising this workflow Expand the workflow to post to other social media platforms supported by Blotato, such as Facebook or LinkedIn. Instead of posting immediately, add a human-in-the-loop approval step by sending the AI-generated draft to Slack or email for review before publishing. Replace the Schedule Trigger with a Webhook Trigger to generate and post relevant content based on external events, such as "when a new blog post is published."

This n8n template demonstrates how to use AI to capture, qualify, and route inbound leads automatically from email or web forms. It extracts key business information using AI, scores the lead based on your ideal customer profile, creates CRM records, notifies your team on Slack, and logs all activity—including failures—to Google Sheets. Use cases include: automating sales inboxes, qualifying form leads for agencies or SaaS products, routing high-fit prospects to the right territory owner, and keeping your sales and ops teams aligned without manual data entry. Good to know The OpenAI model is used for lead data extraction and will incur a small cost per run depending on volume. This workflow supports either Salesforce or HubSpot as the CRM system—select which one in the configuration node. You’ll need valid credentials for Gmail (or another email service), OpenAI, Slack, Google Sheets, and your chosen CRM before running. How it works Triggers: A Gmail trigger polls for new inbound emails. A Webhook node receives submissions from any online form. Both sources merge into a single pipeline. Validation: Incoming data is checked for required fields (email or text). Invalid entries are routed to the Dead Letter Queue (DLQ) for review. AI Extraction: The OpenAI node extracts structured fields like company name, size, industry, role, region, problem statement, and budget signals from free-form text. Parsing & Scoring: The AI output is parsed, then a code node calculates a 0–100 lead score based on transparent criteria—industry, size, role, problem clarity, and budget mentions. It also assigns a lead tier (Hot, Warm, Cold, Unqualified). CRM Routing: Depending on your configuration, the workflow creates a Salesforce lead (default) or can be easily adapted for HubSpot. Territory or CRM owner routing can be extended here. Slack Notification: A rich Slack message summarizes the lead score and reasoning and includes a “Create intro email” button for quick action. Logging: All successful leads are logged to Google Sheets for reporting. Any failed or invalid leads are logged separately to the DLQ tab for auditing. How to use Configure your credentials for Gmail, OpenAI, Slack, Google Sheets, and your CRM. Open the Workflow Configuration node and fill in your target industries, buyer roles, company size, Slack channel ID, Google Sheets URL, and CRM choice. Create corresponding tabs in your Google Sheet for Leads and DLQ. Test by sending a sample email or form submission, then watch the workflow extract, score, route, and notify automatically. Requirements OpenAI account for text extraction Gmail (or other email provider) for the email trigger Slack for lead notifications Google Sheets for logging leads and DLQ entries Salesforce or HubSpot account for CRM integration Customizing this workflow This template can be expanded in many ways: Add HubSpot routing on the first Switch output. Integrate a Slack button handler to auto-generate intro emails. Add retry and backoff logic for resilience. Modify the scoring rubric in the code node to match your unique ICP. Connect additional sources, such as LinkedIn forms or landing page builders, for omnichannel lead capture.

TalentFlow AI – Bulk Resume Screening with JD Matching Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share. 👤 Who’s it for This workflow is designed for: HR or Talent Acquisition (TA) teams handling multiple candidates per role Recruiters who want AI-assisted resume screening to save time and reduce bias Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets ⚙️ How it works / What it does HR/TA uploads multiple candidate resumes and selects a job role Each resume is: Uploaded to Google Drive Parsed with GPT-4 to extract structured profile data The job description for the selected role is: Retrieved from Google Sheets Downloaded from Drive and parsed The profile + JD are sent to an AI agent to generate: Fit score Strengths & gaps Final recommendation Results are: Appended to the evaluation tracking sheet Optionally shared with the hiring team on Slack Used to trigger emails to qualified or unqualified candidates 🛠️ How to set up Clone or import the workflow into your n8n instance Connect your integrations: Google Sheets (positions & evaluation form) Google Drive (CV & JD folders) OpenAI API (GPT-4) Slack (for notifications) (Optional) SendGrid or SMTP for email notifications Update Google Sheets structure: Positions sheet: maps Job Role → JD file link Evaluation form: stores evaluation results Prepare Drive folders: /cv folder for uploaded resumes /jd folder for job description PDFs 📋 Requirements ✅ n8n (hosted or self-hosted) ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents) ✅ Google Drive + Google Sheets access ✅ Slack workspace + bot token (Optional) SendGrid or email credentials for candidate follow-up 🎨 How to customize the workflow Change the fit score threshold in the Candidate qualified? node Edit Slack message content/formatting to match your company tone Add additional candidate metadata to Sheets or Slack messages Use a webhook trigger to integrate with your ATS or job board Swap GPT-4 with Claude or Gemini if you prefer other AI services Expand to include multi-position batch screening logic Happy Hiring! 🚀 Automated with love using n8n

📦 Send Telegram Notifications for New WooCommerce Orders This workflow automatically sends a Telegram notification when an order status in WooCommerce changes to "Processing." Perfect for online store owners who want instant updates on order fulfillment. ⚙️ Set Up Telegram Alerts for WooCommerce Orders Configure WooCommerce Webhook to trigger on order updates. Create a Telegram Bot and obtain the API token. Set Up Telegram Credentials in n8n. Configure the Telegram Node with your chat ID. Activate and Test the workflow by placing a new order. ##💡 Notes You can customize the message format in the 🖋️ Design Message Template node to include additional order details. Contact me on [Telegram]: https://t.me/amir676080 Message structure includes the following details 🆔 Order Number: 11234 👦🏻 Customer Name: John Doe 💵 Amount: 299.99 USD 📅 Order Date: ➖ 25th November 2024 at 14:42 🏙 City: New York 📞 Phone: +1 555-1234 ✍🏻 Order Note: Fast delivery requested 📦 Ordered Products: 🔹 Wireless Earbuds (2 items) 📝 Type: Premium Sound Edition Contact me on [Telegram]: https://t.me/amir676080

🎯 Workflow Goal Still manually checking form responses in your inbox? What if every submission landed neatly in Airtable — and you got a clean Slack message instantly? That’s exactly what this workflow does. No code, no delay — just a smooth automation to keep your team in the loop: Tally → Airtable → Slack Build an automated flow that: receives Tally form submissions, cleans up the data into usable fields, stores the results in Airtable, and automatically notifies a Slack channel. Step 1 – Connect Tally to n8n What we’re setting up A Webhook node in POST mode. Technical Add a Webhook node. Set it to POST. Copy the generated URL. In Tally → Integrations → Webhooks → paste this URL. Submit a test response on your form to capture a sample structure. Step 2 – Clean the data After connecting Tally, you now receive raw data inside a fields[] array. Let’s convert that into something clean and structured. Goal Extract key info like Full Name, Email, Phone, etc. into simple keys. What we’re doing Add a Set node to remap and clean the fields. Technical Add a Set node right after the Webhook. Add new values (String type) manually: Name: Full Name → Value: {{$json"fields"["value"]}} Name: Email → Value: {{$json"fields"["value"]}} Name: Phone → Value: {{$json"fields"["value"]}} (Adapt the indexes based on your form structure.) Use the data preview in the Webhook node to check the correct order. Output You now get clean data like: { "Full Name": "Jane Doe", "Email": "jane@example.com", "Phone": "+123456789" } Step 3 – Send to Airtable ✅ Once the data is cleaned, let’s store it in Airtable automatically. Goal Create one new Airtable row for each form submission. What we’re setting up An Airtable – Create Record node. Technical Add an Airtable node. Authenticate or connect your API token. Choose the base and table. Map the fields: Name: {{$json["Full Name"]}} Email: {{$json["Email"]}} Phone: {{$json["Phone"]}} Output Each submission creates a clean new row in your Airtable table. Step 4 – Add a delay ⌛ After saving to Airtable, it’s a good idea to insert a short pause — this prevents actions like Slack messages from stacking too fast. Goal Wait a few seconds before sending a Slack notification. What we’re setting up A Wait node for X seconds. ✅ Technical Add a Wait node. Choose Wait for X minutes. Step 5 – Send a message to Slack 💬 Now that the record is stored, let’s send a Slack message to notify your team. Goal Automatically alert your team in Slack when someone fills the form. What we’re setting up A Slack – Send Message node. Technical Add a Slack node. Connect your account. Choose the target channel, like #leads. Use this message format: New lead received! Name: {{$json["Full Name"]}} Email: {{$json["Email"]}} Phone: {{$json["Phone"]}} Output Your Slack team is notified instantly, with all lead info in one clean message. Workflow Complete Your automation now looks like this: Tally → Clean → Airtable → Wait → Slack Every submission turns into clean data, gets saved in Airtable, and alerts your team on Slack — fully automated, no extra work.

This workflow integrates Flowise Multi-Agent Chatflows into a custom-branded n8n chatbot, enabling real-time interaction between users and AI agents powered by large language models (LLMs). Key Advantages: ✅ Easy Integration with Flowise: Uses a low-code HTTP node to send user questions to Flowise's API (/api/v1/prediction/FLOWISE_ID) and receive intelligent responses. Supports multi-agent chatflows, allowing for complex, dynamic interactions. 🎨 Customizable Chatbot UI: Includes pre-built JavaScript for embedding the n8n chatbot into any website. Provides customization options such as welcome messages, branding, placeholder text, chat modes (e.g., popup or embedded), and language support. 🔐 Secure & Configurable: Authorization via Bearer token headers for Flowise API access. Clearly marked notes in the workflow for setting environment variables like FLOWISE_URL and FLOW_ID. How It Works Chat Trigger: The workflow starts with the When chat message received node, which acts as a webhook to receive incoming chat messages from users. HTTP Request to Flowise: The received message is forwarded to the Flowise node, which sends a POST request to a Flowise API endpoint (https://FLOWISEURL/api/v1/prediction/FLOWISE_ID). The request includes the user's input as a JSON payload ({"question": "{{ $json.chatInput }}"}) and uses HTTP header authentication (e.g., Authorization: Bearer FLOWSIE_API). Response Handling: The response from Flowise is passed to the Edit Fields node, which maps the output ($json.text) for further processing or display. Set Up Steps Configure Flowise Integration: Replace FLOWISEURL and FLOWISE_ID in the HTTP Request node with your Flowise instance URL and flow ID. Ensure the Authorization header is set correctly in the credentials (e.g., Bearer FLOWSIE_API). Embed n8n Chatbot: Use the provided JavaScript snippet in the sticky notes to embed the n8n chatbot on your website. Replace YOUR_PRODUCTION_WEBHOOK_URL with the webhook URL generated by the When chat message received node. Customize the chatbot's appearance and behavior (e.g., welcome messages, language, UI elements) using the createChat configuration options. Optional Branding: Adjust the sticky note examples to include branding details, such as custom messages, colors, or metadata for the chatbot. Activate Workflow: Toggle the workflow to "Active" in n8n and test the chat functionality end-to-end. Ideal Use Cases: Embedding branded AI assistants into websites. Connecting Flowise-powered agents with customer support chatbots. Creating dynamic, smart conversational flows with LLMs via n8n automation. Need help customizing? Contact me for consulting and support or add me on Linkedin.

What is Elderwatch Elder Watch is a simple system that checks daily vitals — like heart rate, oxygen, and walking symmetry — using data from an iPhone or Apple Watch. If something looks off — say oxygen drops or heart rate spikes — it flags that as “attention required.” And depending on that status, it can either: Email a daily report to a caregiver Or if there’s an alert — trigger a phone call via Twilio Why do we need this Elder Watch can help older people living alone for children or care givers to keey an eye on without obsessively checking apps. It’s useful for clinics that run home-care programs. Requirements Self hosted or cloud N8N Apple health vis iphone/watch Twilio VOIP phone number (to place a call) Workflows Core workflow for getting health data, processing and making a phone call. Twilio workflow to invoke Calls API to place an outbound voice call. twilio workflow { "name": "Twilio Bridge Caller copy", "nodes": [ { "parameters": { "httpMethod": "POST", "path": "twilio-call", "responseMode": "responseNode", "options": {} }, "type": "n8n-nodes-base.webhook", "typeVersion": 2, "position": [ 0, 0 ], "id": "ca3e6c69-3e7f-4d28-b699-4789a6fa2a6d", "name": "Webhook", "webhookId": "eb3d63df-800c-401d-931a-c6fba7d834ae" }, { "parameters": { "respondWith": "text", "responseBody": "={{ $json.body }}", "options": { "responseCode": 200, "responseHeaders": { "entries": [ { "name": "Content-Type", "value": "text/xml" } ] } } }, "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.1, "position": [ 580, 0 ], "id": "6587b7e2-ace8-4e2b-9f4b-ed028a363c25", "name": "Respond to Webhook" }, { "parameters": { "jsCode": "const summary = $input.first().json.query.summary || 'No summary, check mail for critical health info';\n\nreturn [\n {\n json: {\n body: <Response>\n <Say voice=\"alice\">${summary}</Say>\n</Response>\n }\n }\n];\n" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 340, 0 ], "id": "0d4abf87-daf3-4533-8811-64ae61265f5d", "name": "Voice Twilio response" } ], "pinData": { "Webhook": [ { "json": { "headers": { "host": "n8n.domain.com", "user-agent": "curl/8.7.1", "content-length": "0", "accept": "/", "accept-encoding": "gzip, br" }, "params": {}, "query": { "lead": " 44711111111111" }, "body": {}, "webhookUrl": "https://n8n.domain.com/webhook/twilio-call", "executionMode": "production" } } ] }, "connections": { "Webhook": { "main": [ [ { "node": "Voice Twilio response", "type": "main", "index": 0 } ] ] }, "Voice Twilio response": { "main": [ [ { "node": "Respond to Webhook", "type": "main", "index": 0 } ] ] } }, "active": true, "settings": { "executionOrder": "v1" }, "versionId": "b58c5a12-75be-4b1d-b144-8c7251468021", "meta": { "instanceId": "8dc0e8a0878d0086b2f46ef04bb00ae07186c936d82d0f0a67563e9652996d33" }, "id": "RHaKqf8Wqt7fIuGH", "tags": [] } Samples Resources https://www.youtube.com/watch?v=HYk5_jtMlgc Questions/Support Contact me on info@pankstr.com.

Workflow: Auto-Ticket Maker ⚡ About the Creators This workflow was created by Varritech Technologies, an innovative agency that leverages AI to engineer, design, and deliver software development projects 500% faster than traditional agencies. Based in New York City, we specialize in custom software development, web applications, and digital transformation solutions. If you need assistance implementing this workflow or have questions about content management solutions, please reach out to our team. 🏗️ Architecture Overview This workflow transforms your Slack conversations into complete project tickets, effectively replacing the need for a dedicated PM for task creation: Slack Webhook → Captures team conversation Code Transformation → Parses Slack message structure AI PM Agent → Analyzes requirements and creates complete tickets Memory Buffer → Maintains conversation context Slack Output → Returns formatted tickets to your channel Say goodbye to endless PM meetings just to create tickets! Simply describe what you need in Slack, and our AI PM handles the rest, breaking down complex projects into structured epics and tasks with all the necessary details. 📦 Node-by-Node Breakdown flowchart LR A[Webhook: Slack Trigger] --> B[Code: Parse Message] B --> C[AI PM Agent] C --> D[Slack: Post Tickets] E[Memory Buffer] --> C F[OpenAI Model] --> C Webhook: Slack Trigger Type: HTTP Webhook (POST /slack-ticket-maker) Purpose: Captures messages from your designated Slack channel. Code Transformation Function: Parses complex Slack payload structure Extracts: User ID, channel, message text, timestamp, thread information AI PM Agent Inputs: Parsed Slack message Process: Evaluates project complexity Requests project name if needed Asks clarifying questions (up to 2 rounds) Breaks down into epics and tasks Formats with comprehensive structure Ticket Structure: Title Description Objectives/Goals Definition of Done Requirements/Acceptance Criteria Implementation Details Risks & Challenges Testing & Validation Timeline & Milestones Related Notes & References Open Questions Memory Buffer Type: Window Buffer Memory Purpose: Maintains context across conversation Slack Output Posts fully-formatted tickets back to your channel Uses markdown for clean, structured presentation 🔍 Design Rationale & Best Practices Replace Your PM's Ticket Creation Time Let your PM focus on strategy while AI handles the documentation. Cut ticket creation time by 90%. Standardized Quality Every ticket follows best practices with consistent structure, detail level, and formatting. No Training Required Describe your needs conversationally - the AI adapts to your communication style. Seamless Integration Works within your existing Slack workflow - no new tools to learn.

This sample workflow allows you to forward alerts from TheHive 5 to SIGNL4 in order to send reliable alerts to your team. There are two nodes for testing the TheHive connection ("TheHive Read Alerts" and "TheHive Create Alert"). The node "TheHive Webhook Request" will receive requests for new alerts from TheHive. You need to configure the webhook and the notifications in TheHive accordingly. The node "SIGNL4 Send Alert" sends the alert to SIGNL4 and the node "SIGNL4 Resolve Alert" will close the alert in SIGNL4 in case it has been closed in TheHive.