Workflow Templates

Complete MCP server exposing 2 Catalog API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Catalog API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Catalog API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath} • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Product (1 endpoints) • GET /product/{epid}: Get {Epid} 🔧 Product_Summary (1 endpoints) • GET /product_summary/search: Search Product Summaries 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Catalog API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

This workflow automates the restaurant POS (Point of Sale) data management process, facilitating seamless order handling, customer tracking, inventory management, and sales reporting. It retrieves order details, processes payment information, updates inventory, and generates real-time sales reports, all integrated into a centralized system that improves restaurant operations. The workflow integrates various systems, including a POS terminal to gather order data, payment gateways to process transactions, inventory management tools to update stock, and reporting tools like Google Sheets or an internal database for generating sales and performance reports. Who Needs Restaurant POS Automation? This POS automation workflow is ideal for restaurant owners, managers, and staff looking to streamline their operations: Restaurant Owners – Automate order processing, track sales, and monitor inventory to ensure smooth operations. Managers – Access real-time sales data and performance reports to make informed decisions. Staff – Reduce manual work, focusing on providing better customer service while the system handles orders and payments. Inventory Teams – Automatically update inventory levels based on orders and ingredient usage. If you need a reliable and automated POS solution to manage restaurant orders, payments, inventory, and reporting, this workflow minimizes human error, boosts efficiency, and saves valuable time. Why Use This Workflow? End-to-End Automation – Automates everything from order input to inventory updates and sales reporting. Seamless Integration – Connects POS, payment systems, inventory management, and reporting tools for smooth data flow.(if needed) Real-Time Data – Provides up-to-the-minute reports on sales, stock levels, and order statuses. Scalable & Efficient – Supports multiple locations, multiple users, and high order volumes. Step-by-Step: How This Workflow Manages POS Data Collect Orders – Retrieves order details from the POS system, including customer information, ordered items, and payment details. Update Inventory – Decreases inventory levels based on sold items, ensuring stock counts are always accurate. Generate Reports – Compiles sales, revenue, and inventory data into real-time reports and stores them in Google Sheets or an internal database. Track Customer Data – Keeps a log of customer details and order history for better service and marketing insights. Customization: Tailor to Your Needs Multiple POS Systems – Adapt the workflow to work with different POS systems or terminals based on your restaurant setup. Custom Reporting – Modify the reporting format or include specific sales metrics (e.g., daily totals, best-selling items, employee performance). Inventory Management – Adjust inventory updates to include alerts when stock reaches critical levels or needs reordering. Integration with Accounting Software – Connect with platforms like QuickBooks for automated financial tracking. 🔑 Prerequisites POS System Integration – Ensure the POS system can export order data in a compatible format. Payment Gateway API – Set up the necessary API keys for payment processing (e.g., Stripe, PayPal). Inventory Management Tools – Use inventory software or databases that can automatically update stock levels. Reporting Tools – Use Google Sheets or an internal database to store and generate sales and inventory reports. 🚀 Installation & Setup Configure Credentials Set up API credentials for payment gateways and inventory management tools. Import Workflow Import the workflow into your automation platform (e.g., n8n, Zapier). Link POS system, payment gateway, and inventory management systems. Test & Run Process a test order to ensure that data flows correctly through each step. Verify that inventory updates and reports are generated as expected. ⚠ Important Data Privacy – Ensure compliance with data protection regulations (e.g., GDPR, PCI DSS) when handling customer payment and order data. System Downtime – Monitor system performance to ensure that the workflow runs without disruptions during peak hours. Summary This restaurant POS automation workflow integrates order management, payment processing, inventory updates, and real-time reporting, enabling efficient restaurant operations. Whether you are running a single location or a chain of restaurants, this solution streamlines daily tasks, reduces errors, and provides valuable insights, saving time and improving customer satisfaction. 🚀

Who this is for The Real Estate Intelligence Tracker is a powerful automated workflow designed for real estate analysts, investors, proptech startups, and market researchers who need to collect and analyze structured data from real estate listings across the web at scale. This workflow is tailored for: Real Estate Analysts** - Tracking property prices, locations, and market trends Investment Firms** - Sourcing high-opportunity listings for portfolio decisions PropTech Developers** - Automating listing insights for SaaS platforms Market Researchers** - Extracting insights from competitive housing data Growth Teams** - Monitoring geographic property trends and pricing fluctuations What problem is this workflow solving? Collecting structured real estate listing data from property websites is difficult due to bot protections and unstructured HTML content. Manual data collection is slow and error-prone, and traditional scrapers often get blocked or miss context. This workflow solves: Automated bypass of anti-bot protection using Bright Data Web Unlocker Conversion of unstructured HTML content into clean text using a Markdown-to-text LLM pipeline Structured extraction of key listing data like price, location, property type, and features using OpenAI Aggregation and delivery of insights to Google Sheets, local storage, and webhook-based alerts What this workflow does Convert to Text: Transforms scraped HTML/markdown into clean text using a Basic LLM Chain Structured Data Extraction: Uses OpenAI GPT-4o with the Information Extractor node to parse property attributes (price, address, area, type, etc.) Aggregate & Merge: Combines data from multiple pages or listings into a cohesive structure Outbound Data Handling: Google Sheets** – Appends the structured real estate data for further analysis Save to Disk** – Persists structured JSON/text data locally Webhook Notification** – Sends data alerts or summaries to any third-party platform Pre-conditions You need to have a Bright Data account and do the necessary setup as mentioned in the "Setup" section below. You need to have an OpenAI Account. 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 Sheet Credentials with your own account. Follow this documentation - Set Google Sheet Credential In n8n, configure the OpenAi account credentials. Ensure the URL and Bright Data zone name are correctly set in the Set URL, Filename and Bright Data Zone node. Set the desired local path in the Write a file to disk node to save the responses. How to customize this workflow to your needs Target Multiple Sites or Locations Update the Bright Data URL node dynamically with a list of regional real estate websites Loop through different city/state filter URLs Customize Extracted Fields Modify the Information Extractor prompt to extract fields like: Property size, number of bedrooms/bathrooms Days on market Nearby amenities or schools Agent contact details Integrate with More Destinations Add nodes to export data to Notion, Airtable, HubSpot, or your custom database Generate automated reports using PDF generators and email them Data Quality and Logging Add validation checks (e.g., missing price or address) Save intermediate files (markdown, raw HTML, JSON output) to disk for audit purposes

The Chinese Translator workflow automates the translation of text into Chinese characters, pinyin, and English translations via Line Messaging API. This workflow leverages OpenRouter.ai to call advanced language models such as Qwen for accurate translations and ensures smooth user interaction by providing loading animations and timely replies. Purpose This workflow aims to Provide users with real-time translations of input text into Chinese characters, pinyin, and English Deliver seamless user experience through interactive features like loading animations and quick reply messages Enable easy integration with Line Messaging API for scalable deployment Key Features Real-Time Translation : Translates user-inputted text instantly using OpenRouter.ai's standardized API. Comprehensive Output : Delivers Chinese characters, pinyin, and English translations for each word or phrase. Interactive User Experience : Incorporates loading animations to inform users that the workflow is processing their request. Line Integration : Utilizes Line Webhooks and Reply APIs to facilitate communication between users and the translation service. Data Flow Receiving Input Node: Line Webhook Captures incoming messages from Line users. Extracts the text content and reply token from the webhook payload. Loading Animation Node: Line Loading Animation Sends a loading animation back to the user, indicating that the workflow is processing the request. Enhances user experience by providing immediate feedback. Translation Processing Node: Use OpenRouter Sends the extracted text to OpenRouter.ai's API, utilizing the Qwen model for translation. Requests Chinese characters, pinyin, and English translations for the input text. Sending Response Node: Line Reply Formats the translation results into a readable text message. Sends the translated text back to the user via Line's Reply API. Setup Instructions Prerequisites Line Developer Account : Create a Line channel to obtain necessary credentials for webhooks and messaging. OpenRouter.ai Account : Set up an account and configure access to utilize their language models. Steps to Configure Set Up Line Webhook : Navigate to the Line Developers Console and create a new webhook URL. Copy the generated webhook URL and paste it into the Line Webhook node in n8n. Configure OpenRouter.ai : Obtain API credentials from OpenRouter.ai and integrate them into the Use OpenRouter node within the workflow. Adjust Workflow Settings : Ensure the timezone is set to Asia/Bangkok . Verify that all nodes are correctly connected and configured with appropriate credentials. Intended Audience This workflow is ideal for: Language Learners : Seeking quick translations and pronunciation guides for Chinese language studies. Travelers : Looking to communicate effectively while traveling in Chinese-speaking regions. Businesses : Aiming to provide multilingual support to customers and clients. Benefits Enhanced Learning : Provides comprehensive translations, including pinyin, aiding in language acquisition. User-Friendly Interface : Real-time loading animations and prompt replies ensure a smooth user experience. Scalable Deployment : Easily integrates with Line's extensive user base for widespread accessibility.

🛠️ CircleCI Tool MCP Server Complete MCP server exposing all CircleCI Tool operations to AI agents. Zero configuration needed - all 3 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every CircleCI Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n CircleCI Tool tool with full error handling 📋 Available Operations (3 total) Every possible CircleCI Tool operation is included: 🔧 Pipeline (3 operations) • Get a pipeline • Get many pipelines • Trigger a pipeline 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native CircleCI Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every CircleCI Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

This n8n template monitors active support issues in Linear.app to track the mood of their ongoing conversation between reporter and assignee using Sentiment Analysis. When sentiment dips into the negative, a notification is sent via Slack to alert the team. How it works A scheduled trigger is used to fetch recently updated issues in Linear using the GraphQL node. Each issue's comments thread is passed into a simple Information Extractor node to identify the overall sentiment. The resulting sentiment analysis combined with the some issue details are uploaded to Airtable for review. When the template is re-run at a later date, each issue is re-analysed for sentiment Each issue's new sentiment state is saved to the airtable whilst its previous state is moved to the "previous sentiment" column. An Airtable trigger is used to watch for recently updated rows Each matching Airtable row is filtered to check if it has a previous non-negative state but now has a negative state in its current sentiment. The results are sent via notification to a team slack channel for priority. Check out the sample Airtable here: https://airtable.com/appViDaeaFw4qv9La/shrq6HgeYzpW6uwXL How to use Modify the GraphQL filter to fetch issues to a relevant issue type, team or person. Update the Slack channel to ensure messages are sent to the correct location or persons. The Airtable also serves to give a snapshot of Sentiment across support tickets for a given period. It's possible to use this to assess the daily operations. Requirements Linear for issue tracking (but feel free to use another system if preferred) Airtable for Database OpenAI for LLM and Sentiment Analysis Customising the workflow Add more granular levels of sentiment to reduce the number of alerts. Explore different types of sentiment based on issue types and customer types. This may help prioritise alerts and response. Run across teams or categories of issues to get an overview of sentiment across the support organisation.

This automated workflow takes a static image and a textual prompt and transforms them into an animated video using the MiniMax Hailuo 02 model. It then uploads the generated video to YouTube and TikTok, and updates a Google Sheet with relevant links and metadata. Benefits of This Workflow Fully Automated Pipeline**: From prompt to video to social media publication — all without manual intervention. Scalable Content Creation**: Generate and distribute dozens of videos per hour with minimal human input. Cross-Platform Posting: Automatically pushes content to **YouTube and TikTok simultaneously. SEO Optimization**: Uses AI to generate catchy, keyword-rich video titles that improve visibility. Easy Integration**: Based on Google Sheets for input/output, making it accessible to non-technical users. Time-Efficient**: Batch-processing enabled with scheduled runs every few minutes. Customizable Duration**: Video duration can be adjusted (default is 6 seconds). How It Works Trigger & Data Fetching: The workflow starts either manually or via a scheduled trigger (e.g., every 5 minutes). It checks a Google Sheet for new entries where the "VIDEO" column is empty, indicating pending video generation tasks. Video Creation: For each entry, the workflow extracts the image URL and prompt from the Google Sheet. It sends these inputs to the MiniMax Hailuo 02 to generate a video. The API processes the image and prompt, optimizes the prompt, and creates a short video (default: 6 seconds). Status Monitoring: The workflow polls the API every 60 seconds to check if the video is COMPLETED. Once ready, it retrieves the video URL and uploads the file to Google Drive. YouTube & TikTok Upload: The video is sent to YouTube and TikTok via the Upload-Post.com API (The free plan allows uploads to all platforms except TikTok. To enable, upgrade to a paid plan.). A GPT-generated SEO-optimized title is created for the video. The Google Sheet is updated with the video URL and YouTube link. Set Up Steps Google Sheet Setup: Create a Google Sheet with columns: IMAGE (input image URL), PROMPT (video description), VIDEO (auto-filled), and YOUTUBE_URL (auto-filled). Link the sheet to the workflow using the Google Sheets node. API Keys: Obtain a fal.run API key (for MiniMax Hailuo) and configure the "Authorization" header in the "Create video" node. Get an Upload-Post.com API key (10 free uploads/month) and set it in the "Upload on YouTube/TikTok" nodes. Workflow Configuration: Replace YOUR_USERNAME in the Upload-Post nodes with your profile name (e.g., "test1"). Adjust the video duration (6 or 10 seconds) in the "Create video" node. Set the Schedule Trigger interval (e.g., 5 minutes) to automate checks for new tasks. Execution: Run the workflow manually or let the scheduler process new rows automatically. The system handles video generation, uploads, and Google Sheet updates end-to-end. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Use Case This workflow is beneficial when you're automatically adding new leads to your Pipedrive CRM. Usually, you'd have to manually review each lead to determine if they're a good fit. This process is time-consuming and increases the chances of missing important leads. This workflow ensures every new lead is promptly evaluated upon addition. What this workflow does The workflow runs every 5 minutes. On every run, it checks your new Pipedrive leads and enriches them with Clearbit. It then marks items as enriched and checks if the company of the new lead matches certain criteria (in this case if they are B2B and have more than 100 employees) and sends a Slack alert to a channel for every match. Pre Conditions You must have Pipedrive, Clearbit, and Slack accounts. You also need to set up the custom fields Domain and Enriched at in Pipedrive. Setup Go to Company Settings -> Data fields -> Organization and add Domain as a custom field Go to Company Settings -> Data fields -> Leads and add Enriched at as a custom date field Add your Pipedrive, Clearbit and Slack credentials. Fill the setup node below. To get the ID of your custom domain fields, simply run the Show only custom organization fields and Show only custom lead fields nodes below and copy the keys of your domain, and enriched at fields. How to adjust this workflow to your needs Modify the criteria to suit your definition of an interesting lead. If you only want to focus on interesting leads in Pipedrive, add a node that archives all others. This workflow was built using n8n version 1.29.1

Video Guide I prepared a detailed guide explaining how to build an AI-powered meeting assistant that provides real-time transcription and insights during virtual meetings. Youtube Link Who is this for? This workflow is ideal for business professionals, project managers, and team leaders who require effective transcription of meetings for improved documentation and note-taking. It's particularly beneficial for those who conduct frequent virtual meetings across various platforms like Zoom and Google Meet. What problem does this workflow solve? Transcribing meetings manually can be tedious and prone to error. This workflow automates the transcription process in real-time, ensuring that key discussions and decisions are accurately captured and easily accessible for later review, thus enhancing productivity and clarity in communications. What this workflow does The workflow employs an AI-powered assistant to join virtual meetings and capture discussions through real-time transcription. Key functionalities include: Automatic joining of meetings on platforms like Zoom, Google Meet, and others with the ability to provide real-time transcription. Integration with transcription APIs (e.g., AssemblyAI) to deliver seamless and accurate capture of dialogue. Structuring and storing transcriptions efficiently in a database for easy retrieval and analysis. Real-Time Transcription: The assistant captures audio during meetings and transcribes it in real-time, allowing participants to focus on discussions. Keyword Recognition: Key phrases can trigger specific actions, such as noting important points or making prompts to the assistant. Structured Data Management: The assistant maintains a database of transcriptions linked to meeting details for organized storage and quick access later. Setup Preparation Create Recall.ai API key Setup Supabase account and table create table public.data ( id uuid not null default gen_random_uuid (), date_created timestamp with time zone not null default (now() at time zone 'utc'::text), input jsonb null, output jsonb null, constraint data_pkey primary key (id), ) tablespace pg_default; Create OpenAI API key Development Bot Creation: Use a node to create the bot that will join meetings. Provide the meeting URL and set transcription options within the API request. Authentication: Configure authentication settings via a Bearer token for interacting with your transcription service. Webhook Setup: Create a webhook to receive real-time transcription updates, ensuring timely data capture during meetings. Join Meeting: Set the bot to join the specified meeting and actively listen to capture conversations. Transcription Handling: Combine transcription fragments into cohesive sentences and manage dialog arrays for coherence. Trigger Actions on Keywords: Set up keyword recognition that can initiate requests to the OpenAI API for additional interactions based on captured dialogue. Output and Summary Generation: Produce insights and summary notes from the transcriptions that can be stored back into the database for future reference.

Who is it for Customer service or support teams who want to use their Zendesk articles in other tools. Content/Knowledge managers consolidating or migrating knowledge bases. Ops/automation specialists who want Markdown versions of articles (could be adapted to Notion, Google Sheets, or any Markdown-friendly system). How to get started Download the template and install it on your instance Set Zendesk and Airtable credentials Modify the Zendesk base_url and Airtable's table and base Run the workflow once manually to get your existing articles Finally, modify the Schedule Trigger (by default it runs every 30 days) and activate the workflow Prerequisites Airtable base** set up using this template. It includes the fields Title, Content, URL and Article ID. Zendesk account** with API access (read permissions for help center articles) Zendesk API credentials** (see instructions below) Airtable API credentials** (see instructions below) Getting Your Credentials Airtable: Sign up or log in to Airtable. Go to your account settings and generate a Personal Access Token (recommended scopes: data.records:read, data.records:write). In n8n, create new Airtable credentials using this token. Zendesk: Log in to your Zendesk dashboard. Go to Admin Center > Apps and Integrations > Zendesk API. Enable “Token Access,” and create an API token. In n8n, add Zendesk credentials with your Zendesk domain, email, and the API token. How it works 1. Triggers Manual:* For first setup, use the Manual Trigger to fetch *all** existing articles. Scheduled:* Automatically runs every N days to fetch *only new or updated** articles since the last run. 2. Fetch Articles from Zendesk Calls the Zendesk Help Center API, using pagination to handle large volumes. 3. Extract and Prepare Data Splits out each article, then collects fields: id, url, title, and body. Converts the article body from HTML to Markdown (for portability and easier reuse). 4. Upsert Into Airtable Inserts new articles, or updates existing ones (using Article ID as the unique key). Fields stored: Title, Content (Markdown), URL, Article ID. Airtable Template Use this Airtable template as your starting point. Make sure the table has columns: Title, Content, URL, Article ID. You can add more depending on your needs. Example Use Cases Migrating Zendesk articles to another knowledge base. Building an internal knowledge hub in Airtable or Notion. Creating Markdown backups for compliance or versioning. Service If you need help implementing the template or modifying it, just reach out 💌

How it works This template provides a complete, ready-to-use web application for generating high-quality AI prompts. It features a user-friendly web form where you can describe your goal, and it leverages an AI model (Google Gemini) to create a structured, reusable prompt for you. The workflow is a full-stack application built entirely within n8n: Frontend (The Form): A Form Trigger node creates a beautiful, public-facing web form. Here, a user describes the prompt they need and selects which structural components to include (like system instructions, examples, or input variables). Backend (The AI Logic): A LangChain Chain node takes the user's request and constructs a "meta-prompt"—a set of instructions for the AI on how to generate the final prompt. The Google Gemini node executes this meta-prompt, creating a well-structured output with clear sections and tags. The Result (The Webpage): After generation, the user is automatically redirected to a new URL. This URL is handled by another Webhook node, which serves a custom-coded HTML page. This beautiful, dark-themed webpage displays the generated prompt and includes a one-click "Copy" button, making it easy to use the result immediately. This template is a perfect example of how to build interactive web tools with n8n, combining a user interface, backend logic, and a dynamic web response in a single workflow. Set up steps Setup time: ~1-3 minutes This workflow requires a Google AI credential to function. Configure Google AI Credentials: This workflow uses a Google Gemini model. You will need a Google AI API key. In n8n, go to Credentials and click Add credential. Search for Google Gemini and enter your API key. Go back to the workflow, open the Gemini 2.5 Flash node, and select your newly created credential from the dropdown. Activate the Workflow: Click the Active toggle in the top-right corner to turn the workflow on. Access Your Prompt Maker: Open the Prompt Request (Form Trigger) node. Copy the Public URL provided. This is the link to your new web application! Open the link in your browser, fill out the form, and see the magic happen. Note: This workflow uses environment variables like {{ $env.WEBHOOK_URL }} to build the redirect URL. These are typically set automatically by n8n and should work out-of-the-box on most standard n8n setups.

This workflow connects Telegram to Midjourney through GoAPI, enabling automated image generation and upscaling directly from chat. How it Works Telegram Command Trigger**: The workflow activates upon receiving a message in Telegram. Image Generation**: Your prompt is sent to GoAPI, which then generates an image using Midjourney. Upscale Selection**: You receive the generated image and select an option for upscaling. Image Upscaling**: The selected image is upscaled via GoAPI. Notifications and Logs**: Progress updates are sent to Telegram, and all images are logged in Discord. Set Up Steps Create a Telegram Bot and update credentials in Telegram nodes. Create a GoAPI account, obtain an API key, and update the three HTTP nodes: "Get Generation Task," "Upscale," and "Get Upscale Task". (Optional) Configure the Discord node for logging if desired. Setup takes approximately 10-15 minutes. Detailed descriptions are available in sticky notes within the workflow.