Workflow Templates

This workflow performs various Git operations. It starts with a manual trigger, sets the local repository path, decodes a file and then updates a file's content, adds, commits, and pushes changes to a GitHub repository, and finally pulls changes. The upper branch of the workflow retrieves a specific file ("README.md") from a GitHub repository ("git_push_article") owned by "teds-tech-talks." It then decodes the file's binary data into readable text using a code node. The decoded content is used to update the file by adding a timestamp and data. Finally, the modified file is pushed back to the repository using a GitHub node, completing the process of editing and updating the file directly via the workflow. This bottom branch of the workflow makes changes to a local Git repository. It starts by updating the "README.md" file with a timestamp and some content. Then, it adds the modified files, commits the changes with a message, and pushes them to a remote GitHub repository owned by "teds-tech-talks." Additionally, the workflow allows pulling changes from the remote repository into the local repository. The goal is to demonstrate how to perform various Git operations using n8n nodes, including adding, committing, pushing, and pulling changes.

This workflow demonstrates how to use currentRunIndex to get the running index. Function node: This node generates mock data for the workflow. Replace it with the node whose data you want to split into batches. SplitInBatches node: This node splits the data with the batch size equal to 1. Based on your use-case, set the value of the Batch Size. IF node: This node checks the running index. If the running index equals 5 the node returns true and breaks the loop. The node uses the expression {{$node["SplitInBatches"].context["currentRunIndex"];}}, which returns the running index. Set node: This node prints a message Loop Ended. Based on your use-case, connect the false output of the IF node to the input of the node you want to execute if the condition is false.

An intelligent system that monitors social media conversations, identifies high-value engagement opportunities, and generates strategic comments to establish thought leadership while adding genuine value to discussions. Overview This automation workflow leverages Trigify's social listening platform to intelligently identify and respond to social media conversations. It combines AI-powered analysis with strategic comment generation to build authentic thought leadership presence across social platforms. 🔄 Workflow Process 1. Social Listening Webhook Real-time social media monitoring Integrated with Trigify.io social listening platform Monitors conversations across multiple social platforms Captures post content, author details, engagement metrics, and URLs Filters incoming posts by predefined keywords and topics Processes posts in real-time as they're discovered 2. Platform Validation Filter Platform-specific engagement optimization Checks post source (LinkedIn, Twitter, Reddit, etc.) Currently optimized for LinkedIn engagement Filters out non-relevant platforms Maintains platform-specific engagement strategies Routes posts based on platform requirements 3. Post Relevance Analyzer Agent AI-powered opportunity assessment Analyzes post content against expertise domains: Social Media Intelligence Competitive Analysis B2B Marketing Attribution Evaluates value-add potential and audience quality Scores engagement opportunity and confidence levels Identifies natural connection points to demonstrate authority Filters out low-quality or irrelevant conversations Returns structured analysis with TRUE/FALSE relevance decision 4. Engagement Decision Gate Quality control checkpoint Processes AI analysis results Only proceeds with TRUE relevance scores Prevents engagement on inappropriate content Maintains high-quality engagement standards Protects brand reputation through selective filtering 5. Strategic Comment Generator Agent Authentic thought leadership responses Generates comments under 30 words for maximum impact Focuses on tactical advice, strategic insights, or pattern recognition Avoids promotional language or forced statistics Incorporates domain expertise naturally Maintains conversational, helpful tone Uses experience-based insights over generic advice 6. Web Search Integration Enhanced context gathering Optional web search capability for additional context Provides current market insights when needed Supplements comment generation with real-time data Ensures comments are informed and relevant 7. Output Formatting Structured data preparation Compiles post URL, suggested comment, and post summary Formats data for Slack notification system Maintains context across workflow steps Prepares actionable engagement package 8. Slack Notification System Team collaboration and review Sends formatted notifications to #comment-strategy channel Includes post summary, suggested comment, and direct link Provides action buttons (View Post, Copy Comment, Skip) Enables team review before engagement Maintains engagement tracking and decision history 🛠️ Technology Stack n8n**: Workflow orchestration and webhook management Claude Sonnet 4**: Multi-agent AI analysis and content generation Trigify.io**: Social listening and post monitoring platform Slack API**: Team notifications and collaboration OpenAI API**: Optional web search for enhanced context Webhook Integration**: Real-time post processing ✨ Key Features Real-time social media monitoring via Trigify integration AI-powered relevance scoring and quality assessment Strategic comment generation focused on thought leadership Platform-specific engagement optimization (LinkedIn-focused) Team collaboration through Slack notifications Selective engagement to maintain high-quality interactions Expertise-based content analysis across multiple domains Anti-promotional safeguards for authentic engagement 🎯 Ideal Use Cases Perfect for professionals seeking to build authentic thought leadership: B2B Executives** building thought leadership presence Marketing Professionals** demonstrating industry expertise Sales Leaders** engaging prospects through valuable insights Consultants** establishing authority in their domains Business Development Teams** nurturing relationship building Companies** wanting systematic social media engagement Teams** requiring quality control over social interactions Professionals** seeking authentic network growth through value-add 📈 Business Impact Transform passive social listening into active thought leadership: Establishes thought leadership** through strategic engagement Builds authentic professional relationships** naturally Demonstrates expertise** without direct promotion Increases visibility** among target audience Creates networking opportunities** through valuable contributions Maintains consistent social media presence** systematically Scales personal engagement** while preserving authenticity This workflow ensures every engagement adds genuine value while naturally showcasing professional expertise, creating a sustainable approach to social media thought leadership.

Automated Daily AI Summaries from WhatsApp Groups using a Custom AI Agent Transform your WhatsApp group conversations into actionable business intelligence through automated AI analysis and daily reporting. This workflow eliminates manual conversation monitoring by capturing messages in real-time, processing voice notes, and delivering structured insights directly to your team. Overview This workflow provides complete conversation intelligence automation from message capture to insight delivery. It eliminates manual monitoring, analysis, and reporting by using Evolution API integration, OpenAI transcription, and advanced LLM analysis for hands-free business intelligence that scales your team's awareness of important discussions. Core Function: Autonomous conversation analysis that transforms WhatsApp group chatter into structured business insights with zero manual intervention, maintaining consistent daily reporting while capturing emerging opportunities and trends before your competition. Key Capabilities Real-time message capture - Monitors multiple WhatsApp groups simultaneously with instant processing and smart filtering Voice message transcription - Automatic conversion of audio messages to searchable text using OpenAI Whisper AI-powered insight extraction - Advanced LLM analysis identifies trends, opportunities, and actionable information while filtering noise Automated daily reporting - Scheduled intelligence summaries delivered directly to your team via WhatsApp Multi-group organization - Separate tracking and analysis for different communities with unified reporting Smart content filtering - AI agent trained to focus on business-relevant discussions (AI, automation, tech trends, opportunities) Tools Used n8n: Workflow orchestration managing the entire intelligence pipeline from capture to delivery Evolution API: WhatsApp Business API integration for real-time message monitoring and sending OpenAI Whisper: Voice message transcription ensuring no important audio content is missed OpenRouter/GPT-4.1: Advanced AI analysis for intelligent insight extraction and content filtering Google Sheets: Organized message storage with timestamps and metadata for historical analysis Custom AI Agent: "WhatsOn" - specialized business intelligence detective for tech and automation insights How to Install Import the Workflow: Download the JSON file and import into your n8n instance Configure Evolution API: Set up WhatsApp integration and webhook endpoints for message capture API Credentials Setup: Add OpenAI, OpenRouter, and Google Sheets credentials in n8n Group Configuration: Update group IDs in the "Set Info" node with your monitored groups Google Sheets Setup: Create organized spreadsheet with separate tabs for each group Schedule Configuration: Set your preferred daily summary delivery time Test Execution: Run manual test to verify message capture and AI analysis work correctly Use Cases Business Intelligence Automation: Stay informed about industry discussions without manual monitoring Opportunity Detection: Identify emerging trends, tools, and business opportunities in real-time Team Knowledge Sharing: Automated distribution of relevant insights from multiple communities Competitive Intelligence: Monitor industry discussions to stay ahead of market developments Community Management: Track engagement patterns and important conversations across groups Voice Message Processing: Ensure audio-based insights aren't lost in team communications Setup Requirements Evolution API account: WhatsApp Business integration with webhook capabilities OpenAI API: Voice transcription access through Whisper API OpenRouter account: Access to GPT-4.1 for advanced conversation analysis Google Sheets: Message storage and organization with proper permissions configured WhatsApp Groups: Access to business or professional groups with relevant discussions Total setup time: 15-20 minutes once all API accounts are properly configured. How to Customize Analysis Focus: Modify the AI agent's system prompt to target your industry or specific topics. Adjust keyword priorities, conversation themes, or insight categories based on your business needs. Group Management: Add additional groups by extending the Switch node logic, creating new Google Sheets tabs, and updating group ID variables. Scale from 3 to unlimited group monitoring. Delivery Schedule: Change summary frequency from daily to weekly, multiple times per day, or custom schedules. Add multiple delivery destinations for different team segments. AI Intelligence: Customize the "WhatsOn" agent personality, adjust insight priorities, modify filtering criteria, or add sentiment analysis for deeper conversation understanding. Storage & Organization: Modify Google Sheets structure, add custom metadata fields, integrate with other databases, or connect to business intelligence dashboards for advanced analytics. Advanced Features Smart Voice Processing Automatically transcribes voice messages to text using OpenAI's Whisper API, ensuring critical audio-based discussions are captured and analyzed alongside text conversations. Intelligent Content Filtering The AI agent is specifically trained to identify valuable business insights while filtering out casual conversation, ensuring your daily summaries focus on actionable information that drives decisions. Multi-Fragment Delivery System Large intelligence summaries are automatically broken into properly formatted WhatsApp messages with natural pacing to avoid delivery issues and improve readability. Historical Analysis Capability All conversations are stored with full metadata in Google Sheets, enabling historical trend analysis, keyword tracking, and long-term pattern recognition for strategic planning. Ready to transform group conversations into competitive intelligence? This template converts casual WhatsApp discussions into structured business insights delivered automatically to your team, ensuring you never miss important industry developments or opportunities. Google Sheets Template The workflow includes a pre-configured structure for tracking: Message timestamps and sender information Full conversation content with voice transcriptions Group-specific organization and categorization Daily summary delivery logs and performance metrics Was this helpful? Let me know! I truly hope this WhatsApp intelligence system helps streamline your team's awareness of important conversations. Your feedback helps me create better automation resources for the n8n community. Ready to Build Something Great? If you're looking to take your n8n skills or business automation to the next level, I can help. 🎓 n8n Coaching: Want to become an n8n pro? I offer one-on-one coaching sessions to help you master workflows, tackle specific problems, and build with confidence. ➡️ Book a Coaching Session 💼 n8n Consulting: Have a complex project, an integration challenge, or need a custom workflow built for your business? Let's work together to create a powerful automation solution. ➡️ Inquire About Consulting Services Stay Updated on Automation For more content automation strategies, AI workflow tips, and business automation insights: Follow me on LinkedIn Happy Automating! Daniel Lianes

This n8n workflow is designed for working with the WhatsApp Business platform. It allows to send custom replies via WhatsApp in response to incoming user messages. 💡 Take a look at the step-by-step tutorial on how to create a WhatsApp bot. The workflow consists of two parts: The first Verify webhook sends back verification challenge string. You will need this part during the setup process on the Meta for Developers portal: Select your App Go to WhatsApp Configuration Click on the Edit button in the Webhook session Enter your production webhook URL, provide Verify token (can be any text string) Remember to activate the n8n workflow! Finally press "Verify and save" Once the webhook is verified, the Respond webhook receives various POST requests from Meta regarding WhatsApp messages (user messages and status notifications). The workflow checks whether the incoming JSON contains a user message. If this is the case, it sends the text message back to the user. This is a custom message, not a WhatsApp Business template.

Ibm Granite Granite Speech 3.3 8b Text Generator Description Granite-speech-3.3-8b is a compact and efficient speech-language model, specifically designed for automatic speech recognition (ASR) and automatic speech translation (AST). Overview This n8n workflow integrates with the Replicate API to use the ibm-granite/granite-speech-3.3-8b model. This powerful AI model can generate high-quality text content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Optional Parameters seed** (integer, default: None): Random seed. Leave blank to randomize the seed. audio** (array, default: None): Audio inputs for the model. top_k** (integer, default: 50): The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering). top_p** (number, default: 0.9): A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751). prompt** (string, default: ): User prompt to send to the model. max_tokens** (integer, default: 512): The maximum number of tokens the model should generate as output. min_tokens** (integer, default: 0): The minimum number of tokens the model should generate as output. temperature** (number, default: 0.6): The value used to modulate the next token probabilities. chat_template** (string, default: None): A template to format the prompt with. If not provided, the default prompt template will be used. system_prompt** (string, default: None): System prompt to send to the model.The chat template provides a good default. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate text content Access the generated output from the final node API Reference Model: ibm-granite/granite-speech-3.3-8b API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of text generation parameters

Ndreca Hunyuan3d 2 Test AI Generator Description None Overview This n8n workflow integrates with the Replicate API to use the ndreca/hunyuan3d-2-test model. This powerful AI model can generate high-quality other content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters image** (string): Input image for generating 3D shape Optional Parameters seed** (integer, default: 1234): Random seed for generation steps** (integer, default: 50): Number of inference steps num_chunks** (integer, default: 200000): Number of chunks for mesh generation max_facenum** (integer, default: 40000): Maximum number of faces for mesh generation guidance_scale** (number, default: 5.5): Guidance scale for generation octree_resolution** (string, default: 512): Octree resolution for mesh generation remove_background** (boolean, default: True): Whether to remove background from input image How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate other content Access the generated output from the final node API Reference Model: ndreca/hunyuan3d-2-test API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of other generation parameters

Tags*: Supply Chain, Logistics, Route Planning, Transportation, GPS API Context Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting. I help companies improve their logistics operations using data, AI, and automation to reduce costs and minimize environmental footprint. > Let’s use n8n to build smarter and greener transport operations! 📬 For business inquiries, you can add find me on LinkedIn Who is this template for? This workflow is designed for logistics and transport teams who want to automate distance and travel time calculations for truck shipments. Ideal for: Control tower dashboards Transport cost simulations Route optimization studies How does it work? This n8n workflow connects to a Google Sheet where you store city-to-city shipment lanes, and uses the OpenRouteService API to calculate: 📏 Distance (in meters) ⏱️ Travel time (in seconds) 🪪 Number of route steps Steps: ✅ Load departure/destination city coordinates from a Google Sheet 🔁 Loop through each record 🚚 Query OpenRouteService using the truck (driving-hgv) profile 🧾 Extract and store results: distance, duration, number of steps 📤 Update the Google Sheet with new values What do I need to get started? This workflow is beginner-friendly and requires: A Google Sheet with route pairs (departure and destination coordinates) A free OpenRouteService API key 👉 Get one here Next Steps 🗒️ Follow the sticky notes inside the workflow to: Select your sheet Plug in your API key Launch the flow! 🎥 Check the Tutorial 🚀 You can customize the workflow to: Add CO2 emission estimates for Sustainability Reporting Connect to your TMS via API or EDI This template was built using n8n v1.93.0 Submitted: June 1, 2025

Streamline client onboarding and project setup from hours to minutes with AI-driven automation. This intelligent workflow eliminates manual coordination, builds proposals, creates projects in Asana, welcomes clients on Slack, and logs everything — ensuring 90% faster onboarding and zero dropped steps. What This Workflow Does Transforms your client onboarding from scattered tools and emails into one seamless automation: 📝 Capture Client Details – Jotform intake form collects client, company, and project information. 🧠 AI-Powered Analysis – LangChain AI Agent analyzes the project scope, estimates effort, and recommends team composition. 📄 Generate Proposal – Automatically builds a professional HTML proposal summarizing goals, timeline, and estimated hours. 🗂️ Create Asana Project – Generates a new project with all key details, milestones, and assigned team members. 💬 Slack Collaboration – Creates a dedicated Slack channel, sends welcome messages, and introduces the project team. 📧 Welcome Email – Sends a personalized onboarding email to the client with project summary and next steps. 💼 CRM Sync – Creates or updates a HubSpot contact with complete project and client information. 📊 Audit Logging – Logs all onboarding activity to Google Sheets for centralized record-keeping. Key Features 🤖 AI Proposal Generation – Uses LangChain AI to generate smart project summaries and resource plans. ⚙️ End-to-End Automation – From form submission to project creation, communication, and CRM logging. 💬 Smart Slack Setup – Automatic channel creation and messaging for internal coordination. 📧 Personalized Client Emails – Beautifully formatted, professional onboarding emails. 🗂️ Asana Integration – Project creation with dynamic task templates and priorities. 📊 Google Sheets Logging – Instant audit trail for every client submission and generated proposal. 💼 CRM Integration – Automatically syncs client data with HubSpot for sales and account tracking. Perfect For 🚀 Agencies & Service Providers – Automate client onboarding, proposal creation, and task setup. 🏢 Consultancies – Quickly turn client requests into structured projects with assigned resources. 💻 Freelancers & Creators – Impress clients with AI-built proposals and instant communication. 📈 Growing Teams – Scale onboarding without extra admin or coordination time. 🧠 Operations Teams – Ensure consistency and transparency across all onboarding activities. What You’ll Need Required Integrations 🧾 Jotform – Client intake form (project details, budget, company info). Create your form for free on Jotform using this link 🤖 AI Agent – For analyzing project scope and building proposals. 🗂️ Asana – Project creation and task assignment. 💬 Slack – For automated client channel creation and internal communication. 📧 Gmail – For onboarding and proposal emails. 💼 HubSpot – CRM contact creation and project linkage. 📊 Google Sheets – For logging all onboarding and AI results. Optional Enhancements 📄 PDF Generation (PDF Munk) – Convert AI-generated proposals into downloadable PDFs. 💬 Slack Interactive Approvals – Add buttons for internal review before client communication. 📈 Performance Dashboard – Connect Google Sheets data to Looker Studio for tracking onboarding times. 🌍 Multilingual Support – Add translation nodes for international clients. 🔐 File Attachments – Send proposal PDFs or onboarding kits automatically via Gmail. Quick Start 1️⃣ Import Template – Copy and import the JSON file into your n8n workspace. 2️⃣ Set Up Jotform – Create a form with fields for client name, company, project name, budget, and requirements. 3️⃣ Add Credentials – Connect Jotform, AI Agent, Asana, Slack, Gmail, HubSpot, and Google Sheets. 4️⃣ Configure Sheet ID – Replace YOUR_SHEET_ID in the Google Sheets node. 5️⃣ Customize Proposal HTML – Edit AI prompt and branding to reflect your company’s style. 6️⃣ Test Workflow – Submit a test form and verify Slack, Asana, Gmail, and Sheets outputs. 7️⃣ Deploy – Activate workflow and share the Jotform link with your sales or operations team. Customization Options 1️⃣ Proposal Branding – Customize proposal HTML with logos, brand colors, and formatting. 2️⃣ AI Prompt Tuning – Refine the LangChain AI prompt to match your tone or project style. 3️⃣ Task Templates – Adjust task names, assignees, and due dates in the Asana creation node. 4️⃣ Slack Messaging – Update welcome message formatting and team introduction details. 5️⃣ CRM Fields – Map additional HubSpot properties for better data tracking. 6️⃣ Sheet Logging – Add more columns for tracking team recommendations or proposal scores. Expected Results ⚡ 90% Faster Onboarding – Reduce manual setup from hours to minutes. 🤖 AI Precision – Intelligent proposals and team allocations that impress clients instantly. 📈 Zero Missed Steps – Every project automatically created, communicated, and logged. 💬 Seamless Collaboration – Slack, Gmail, and Asana in perfect sync. 🗂️ Complete Transparency – Every onboarding step logged for accountability and improvement. 🏆 Use Cases 🧑‍💼 Marketing & Creative Agencies – Automate creative project scoping and proposal creation. 💻 Software Development Teams – Rapidly assess client tech requirements and allocate developers. 🧾 Consulting Firms – Build data-backed, AI-enhanced proposals for client engagements. 🏢 Corporate PMOs – Standardize project setup and approvals across multiple departments. Pro Tips 💡 Refine AI Prompt – Include examples of past projects to improve proposal quality. 💬 Add Slack Approvals – Insert “manager approval” logic before sending proposals. 📄 Attach PDFs – Use PDF Munk for branded, downloadable proposals. 📊 Track Conversion – Link HubSpot deal stage changes based on Asana progress. 📅 Monitor Efficiency – Use Sheet timestamps to calculate average onboarding time. Learning Resources This workflow demonstrates: AI integration using Agents Multi-app orchestration and data syncing Advanced HTML and email template customization Real-world Asana and Slack API usage CRM syncing and Google Sheets logging Modular, scalable n8n workflow design Workflow Structure Visualization 📝 Jotform Submission ↓ 🧠 AI Project Analysis (Agent) ↓ 📄 Proposal Generation (HTML) ↓ 🗂️ Asana Project Creation ↓ 💬 Slack Channel Setup & Message ↓ 📧 Gmail Welcome Email ↓ 💼 HubSpot Contact Creation ↓ 📊 Google Sheets Log Ready to Revolutionize Client Onboarding? Import this template today and let AI handle the heavy lifting. Your team saves hours, your clients get instant engagement — and your entire process runs flawlessly. ✨

This workflow automates invoice creation using Google Sheets for structured input and Google Docs for templated output — all built inside n8n. 🛠️ Step-by-Step Instructions ### Step 1: Manual Trigger Start the workflow manually for testing or development purposes. ### Step 2: Google Sheets — Load Invoice Data Pulls invoice data from a Google Sheet. 📄 Sheet URL: Copy This Sheet Expected Columns**: Company From Company To Terms Invoice Description Amount > 🔑 Credentials Required: > Connect to Google Sheets OAuth2 API in n8n. > Be sure your sheet is shared with the connected Google account. ### Step 3: Get Invoice Template — Load Google Doc Loads a static Google Docs template containing placeholder values. 🧾 Template URL: Copy This Template Required Placeholders** in the document: FromCompany# ToCompany# Terms# Invoice# Description# Amount# > 🔑 Credentials Required: > Connect to Google Docs OAuth2 API in n8n. ### Step 4: Create New Doc — Make Invoice File Creates a new Google Doc by duplicating the invoice template. Title Format**: Invoice: {{ $json.Invoice }} Destination Folder ID**: 1TnDibwPPPUm3VbmETiqWDVhtaUTLJ6mn (You can change this to your own Google Drive folder) > 🔐 Make sure your Google Docs credential has write access to this folder. ### Step 5: Merge — Combine Data Merges the loaded document and spreadsheet row together for downstream updates. ### Step 6: Insert Content into Doc (Optional) You can insert additional content here if needed. For example, a note, header, or footer pulled from your database or a custom field. ### Step 7: Input Invoice Details — Replace Fields Uses Google Docs API to replace all placeholders from the original template with the actual values. Replacements: | Placeholder | Replaced With | |----------------|------------------------------| | FromCompany# | Company From from sheet | | ToCompany# | Company To from sheet | | Terms# | Terms from sheet | | Invoice# | Invoice number | | Description# | Description of service | | Amount# | Amount of invoice | 📤 Final Output Each row from the Google Sheet results in a completed, branded Google Doc invoice stored in your Drive. 🙋 Need Help? Robert Breen Automation Consultant 🌐 ynteractive.com 📧 robert.j.breen@gmail.com 🔗 LinkedIn 🔒 Required APIs | Service | Purpose | |------------------|--------------------------| | Google Sheets API | Pull structured invoice data | | Google Docs API | Load & modify invoice documents | | n8n OAuth2 | Connect both services securely | Let me know if you'd like a follow-up step to export invoices as PDFs or auto-email them to clients!

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.

Brief Overview This automation template helps you track the latest real estate listings from the LoopNet platform. By using Scrapeless to scrape property listings, n8n to orchestrate the workflow, and Google Sheets to store the results, you can build a real estate data pipeline that runs automatically on a weekly schedule. How It Works Trigger on a Schedule:** The workflow runs automatically every week (can be adjusted to every 6 hours, daily, etc.). Scrape Property Listings:** Scrapeless crawls the LoopNet real estate website and returns structured Markdown data. Extract & Parse Content:** JavaScript nodes use regex to parse property titles, links, sizes, year built from Markdown. Flatten Data:** Each property listing becomes a single row with structured fields. Save to Google Sheets:** Property data is appended to your Google Sheet for easy analysis, sharing, and reporting. Features No-code, automated real estate listing scraper. Scrapes and structures the latest commercial property listings (for sale or lease). Saves structured listing data directly to Google Sheets. Fully automated, scheduled scraping—no manual scraping is required. Extensible: Add filters, deduplication, Slack/Email notifications, or multi-city scraping. Requirements Scrapeless API Key:** Sign up on the Scrapeless Dashboard. Go to Settings → API Key Management → Create API Key, then copy the generated key. n8n Instance:** Self-hosted or n8n.cloud account. Google Account:** For Google Sheets API access. Target Site:** This template is configured for LoopNet real estate listings but can be adapted for other property platforms like Crexi. Installation Deploy n8n on your preferred platform. Install the Scrapeless node from the community marketplace. Import this workflow JSON file into your n8n workspace. Create and add your Scrapeless API Key in n8n’s credential manager. Connect your Google Sheets account in n8n. Update the target LoopNet URL and Google Sheet details. Usage This automated real estate scraper is ideal for: | Industry / Role | Use Case | | ---------------------- | ----------------------------------------------------------------- | | Real Estate Agencies | Monitor new commercial properties and streamline lead generation. | | Market Research Teams | Track market dynamics and property availability in real-time. | | BI/Data Analysts | Automate data collection for dashboards and market insights. | | Investors | Keep tabs on the latest commercial property opportunities. | | Automation Enthusiasts | Example use case for learning web scraping + automation. | Output Example