Workflow Templates

You can turn messy business card photos into organized contact data automatically. With this workflow, you can upload a business card photo to Slack and instantly capture the contact details into Google Sheets using OCR. No more manual typing—each new card is scanned, structured, saved, and confirmed back in Slack, making contact management fast and effortless. How it works Slack Trigger – The workflow starts when a business card photo is uploaded to Slack. HTTP Request – The uploaded image is fetched from Slack. AI/OCR Parsing – The card image is analyzed by an AI model and structured into contact fields (name, company, email, phone, etc.). Transform Data – The extracted data is cleaned and mapped into the correct format. Google Sheets – A new row is appended to your designated Google Sheet, creating an organized contact database. Slack Notification – Finally, a confirmation message is sent back to Slack to let you know the contact has been successfully saved. How to use Copy the template into your n8n instance. Connect your Slack account to capture uploaded images. Set up your Google Sheets connection and choose the spreadsheet where contacts should be stored. Adjust the Contact Information extraction node if you want to capture custom fields (e.g., job title, address). Deploy and test: upload a business card image in Slack and confirm it’s added to Google Sheets automatically. Requirements n8n running (cloud). A Slack account with access to the channel where photos will be uploaded. A Google Sheets account with a target sheet prepared for storing contacts. AI/OCR capability enabled in your n8n (e.g., OpenAI, Google Vision, or another OCR/LLM provider). Basic access rights in both Slack and Google Sheets to read and write data.

Summary Chat with your AI agent in Telegram. It remembers important facts about you in Airtable, can transcribe your voice messages, search the web, read and manage Google Calendar, fetch Gmail, and query Notion. Responses are grounded in your recent memories and tool outputs, then sent back to Telegram. What this workflow does Listens to your Telegram messages (text or voice) Maintains short-term chat memory per user and long-term memory in Airtable Decides when to save new facts about you (auto “Save Memory” without telling you) Uses tools on demand: Web search via SerpAPI Google Calendar: list/create/update/delete events Gmail: list and read messages Notion: fetch database info Transcribes Telegram voice notes with OpenAI and feeds them to the agent Combines live tool results + recent memories and replies in Telegram Apps and credentials Telegram Bot API: personal_bot xAI Grok: Grok-4 model for chat OpenAI: speech-to-text (transcribe audio) Airtable: store long-term memories Google Calendar: calendar actions Gmail: email actions Notion: knowledge and reading lists SerpAPI: web search Typical use cases Personal assistant that remembers preferences, decisions, and tasks Create/update meetings by chatting, and get upcoming events Ask “what did I say I’m reading?” or “what’s our plan from last week?” Voice-first capture: send a voice note → get a transcribed, actionable reply Fetch recent emails or look up info on the web without leaving Telegram Query a Notion database (e.g., “show me the Neurocracy entries”) How it works (node-by-node) Telegram Trigger Receives messages from your Telegram chat (text and optional voice). Text vs Message Router Routes based on message contents: Text path → goes directly to the Agent (AI). Voice path → downloads the file and transcribes before AI. Always also fetches recent Airtable memories for context. Get a file (Telegram) Downloads the voice file (voice.file_id) when present. Transcribe a recording (OpenAI) Converts audio to text so the agent can use it like a normal message. Get memories (Airtable) Searches your “Agent Memories” base/table, filtered by user, sorted by Created. Aggregate (Aggregate) Bundles recent memory records into a single array “Memories” with text + timestamp. Merge (Merge) Combines current input (text or transcript) with the memory bundle before the agent. Simple Memory (Agent memory window) Short-term session memory keyed by Telegram chat ID; keeps the recent 30 turns. Tools wired into the agent SerpAPI Google Calendar tools: Get many events in Google Calendar Create an event in Google Calendar Update an event in Google Calendar Delete an event in Google Calendar Gmail tools: Get many messages in Gmail Get a message in Gmail Notion tool: Get a database in Notion Airtable tool: Save Memory (stores distilled facts about the user) Agent System prompt defines role, tone, and rules: Be a friendly assistant. On each message, decide if it contains user info worth saving. If yes, call “Save Memory” to persist a short summary in Airtable. Don’t announce memory saves—just continue helping. Use tools when needed (web, calendar, Gmail, Notion). Think with the provided memory context block. Uses xAI Grok Chat Model for reasoning and tool-calling. Can call Save Memory, Calendar, Gmail, Notion, and SerpAPI tools as needed. Save Memory (Airtable) Persists Memory and User fields to “Agent Memories” base; auto timestamp by Airtable. Send a text message (Telegram) Sends the agent’s final answer back to the same Telegram chat ID. Node map | Node | Type | Purpose | |---|---|---| | Telegram Trigger | Trigger | Receive text/voice from Telegram | | Text vs voice router | Flow control | Route text vs voice; also trigger memories fetch | | Get a file | Telegram | Download voice audio | | Transcribe a recording | OpenAI | Speech-to-text for voice notes | | Get memories | Airtable | Load recent user memories | | Aggregate | Aggregate | Pack memory records into “Memories” array | | Merge | Merge | Combine input and memories before agent call | | Simple Memory | Agent memory | Short-term chat memory per chat ID | | xAI Grok Chat Model | LLM | Core reasoning model for the Agent | | Search Web with SerpAPI | Tool | Web search | | Google Calendar tools | Tool | List/create/update/delete events | | Gmail tools | Tool | Search and read email | | Notion tool | Tool | Query a Notion database | | Save Memory | Airtable Tool | Persist distilled user facts | | AI Agent | Agent | Orchestrates tools + memory, produces the answer | | Send a text message | Telegram | Reply to the user in Telegram | Before you start Create a Telegram bot and get your token (via @BotFather). Put your Telegram user ID into the Telegram Trigger node (chatIds). Connect credentials: xAI Grok (model: grok-4-0709) OpenAI (for audio transcription) Airtable (Agent Memories base and table) Google Calendar OAuth Gmail OAuth Notion API SerpAPI key Adjust the Airtable “User” value and the filterByFormula to match your name or account. Setup instructions 1) Telegram Telegram Trigger: additionalFields.chatIds = your_telegram_id download = true to allow voice handling Send a text message: chatId = {{ $('Telegram Trigger').item.json.message.chat.id }} 2) Memory Airtable base/table must exist with fields: Memory, User, Created (Created auto-managed). In Save Memory and Get memories nodes, align Base, Table, and filterByFormula with your setup. Simple Memory: sessionKey = {{ $('If').item.json.message.chat.id }} contextWindowLength = 30 (adjust as needed) 3) Tools Google Calendar: choose your calendar, test get/create/update/delete. Gmail: set “returnAll/simplify/messageId” via $fromAI or static defaults. Notion: set your databaseId. SerpAPI: ensure the key is valid. 4) Agent (AI node) SystemMessage: customize role, name, and any constraints. Text input: concatenates transcript or text into one prompt: {{ $json.text }}{{ $json.message.text }} How to use Send a text or voice message to your bot in Telegram. The agent replies in the same chat, optionally performing tool actions. New personal facts you mention are silently summarized and stored in Airtable for future context. Customization ideas Replace Grok with another LLM if desired. Add more tools: Google Drive, Slack, Jira, GitHub, etc. Expand memory schema (e.g., tags, categories, confidence). Add guardrails: profanity filters, domain limits, or cost control. Multi-user support: store chat-to-user mapping and separate memories by user. Add summaries: a daily recap message created from new memories. Limits and notes Tool latency: calls to Calendar, Gmail, Notion, and SerpAPI add response time. Audio size/format: OpenAI transcription works best with common formats and short clips. Memory growth: periodically archive old Airtable entries, or change Aggregate window. Timezone awareness: Calendar operations depend on your Google Calendar settings. Privacy and safety Sensitive info may be saved to Airtable; restrict access to the base. Tool actions operate under your connected accounts; review scopes and permissions. The agent may call external APIs (SerpAPI, OpenAI); ensure this aligns with your policies. Example interactions “Schedule a 30‑min catch‑up with Alex next Tuesday afternoon.” “What meetings do I have in the next 4 weeks?” “Summarize my latest emails from Product Updates.” “What did I say I’m reading?” (agent recalls from memories) Voice note: “Remind me to call the dentist this Friday morning.” → agent transcribes and creates an event. Tags telegram, agent, memory, grok, openai, airtable, google-calendar, gmail, notion, serpapi, voice, automation Changelog v1: First release with Telegram agent, short/long-term memory, voice transcription, and tool integrations for web, calendar, email, and Notion.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works User Uploads PDF** : The workflow accepts a PDF via webhook. Extract Text** : n8n extracts the text content from the PDF. Summarize with AI** : The extracted text is passed to an AI model (Groq) with OpenAI model for summarization. Generate Audio** : The summary text is sent to a TTS (Text-to-Speech) API (Qwen-TTS-Demo), you can use other free alternatives. Serve Result** : The workflow outputs both Summary and Audio File URL (WAV link) which you can attached to your audioPlayer. This allows users to read or listen to the summary instantly. How to use / Requirements Import Workflow** : Copy/paste the workflow JSON into your n8n instance. Set Up Input Trigger** : If you want users to upload directly you can use webhook or any other trigger. Configure AI Node** : Add your own API key for (Groq / Open AI). Configure TTS Node** : Add credentials for your chosen TTS service. Run Workflow** : Upload a PDF and get back the summary and audio file url. n8n-smart pdf summarizer & voice generator Please reach out to me at Laiba Zubair if you need further assistance with you n8n workflows and automations!

How it works This workflow automatically analyzes meeting effectiveness and provides constructive feedback: • Retrieve meeting minutes: Automatically searches and retrieves meeting minutes from Google Drive using either a Google Docs URL or meeting name • Multi-dimensional analysis: Comprehensively evaluates meeting effectiveness score, speaking time distribution, communication quality (clarity, friendliness, decisiveness, listening), disagreements, and more • Generate actionable feedback: Outputs a structured report in Japanese with specific improvement suggestions and highlights of what went well Set up steps Setup takes approximately 5 minutes: • Connect Google Drive: Grant permission for the workflow to access your meeting minutes by connecting to Google Drive • First run: Enter the meeting minutes URL or meeting name and execute the workflow For detailed setup instructions and step-by-step explanations, please refer to the sticky notes inside your workflow.

How it works: Automatically detects when a new receipt is uploaded to Google Drive. Extracts text from the receipt using OCR. Uses an AI Agent to analyze the extracted data and structure it (e.g., vendor, date, total, tax). Saves the organized receipt data into a Google Sheet for easy tracking. Set up steps: Setup takes around 15–20 minutes. You'll need a Google Drive folder for receipts and a Google Sheet to store results. Configure your Google Drive Trigger, OCR extraction, AI Agent, and Google Sheets connection. Detailed instructions and explanations are included in this n8n Starter Session tutorial series.

Automatically Classify Support Tickets in Zoho Desk with AI with Gemini Transform your customer support workflow with intelligent ticket classification. This automation leverages AI to automatically categorize incoming support tickets in Zoho Desk, reducing manual work and ensuring faster ticket routing to the right teams. How It Works Fetches all tickets from Zoho Desk with pagination support Filters unclassified tickets (where classification field is null) Retrieves complete ticket threads for full conversation context Uses OpenRouter AI (GPT-4, Claude, or other models) to classify tickets into predefined categories Updates tickets in Zoho Desk with accurate classifications automatically Use Cases Customer Support Teams**: Automatically route tickets to specialized departments (billing, technical, sales) Help Desks**: Prioritize urgent issues and categorize feature requests Prerequisites Active Zoho Desk account with API access OpenRouter API account (supports multiple AI models) Basic understanding of OAuth2 authentication Predefined ticket categories in your Zoho Desk setup Setup Steps Time: ~15 minutes Configure Zoho Desk OAuth2 - Follow our step-by-step GitHub guide for OAuth2 credential setup Set up OpenRouter API - Create an account and generate API keys at openrouter.ai Customize classifications - Define your ticket categories (e.g., Technical, Billing, Feature Request, Bug Report) Adapt the workflow - Modify for any field: status, priority, tags, assignment, or custom fields Review API documentation - Check Zoho Desk Search API docs for advanced filtering options Test thoroughly - Run manual triggers before automation Note: This workflow demonstrates proper Zoho Desk API integration, including OAuth2 authentication and pagination handling—two common integration challenges.

This n8n workflow promotes your brand/company/platform by mentioning it in Twitter comments. The responses look human-like, the workflow is robust and designed to avoid bans. Good to know The workflow is configured to maximize efficiency while minimizing costs and ensuring your Twitter account won't get banned or shadow-banned. Generating more than 17 comments per day would require a paid Twitter subscription plan. How it works The User sets a keyword that would be used to find relevant Posts. An AI Agent analyzes each Post and writes a response, promoting User's Brand. After each reponse is submitted, the result is logged in a Report Table for tracking and convenience. Set up steps Set your target keyword and start the workflow. Detailed instructions and tutorials can be found in the workflow's sticky notes. Requirements Twitter and Google accounts. twitterapi.io subscription (used to overcome official Twitter API limitaions). Anthropic subscription (GPT models are also supported, but I personally recommend using Anthropic Claude Sonnet 4 for text generation).

What This Does Automatically finds relevant Reddit posts where your brand can add value, generates helpful AI comments, and sends the best opportunities to your Slack channel for review. Setup Requirements Reddit API credentials OpenAI API key Slack webhook URL Quick Setup Reddit API Create app at reddit.com/prefs/apps (select "script" type) Add client ID and secret to n8n credentials Configure Subreddits Edit the workflow to monitor subreddits relevant to your business: entrepreneur, startups, smallbusiness, [your_niche] AI Prompt Setup Customize the OpenAI node with your brand context: You're helping in [subreddit] discussions. When relevant, mention how [your_product] solves similar problems. Be helpful first, promotional second. Slack Integration Add your webhook URL to get notifications with: Post title and link AI-generated comment Engagement score (1-10) Key Features Smart Filtering**: AI evaluates if a post is worth engaging with Brand-Aware Comments**: Generated responses stay on-brand and helpful Team Review**: All opportunities go to Slack before posting Multiple Subreddits**: Monitor several communities simultaneously Customization Tips Adjust AI Scoring - Modify what makes a "good" opportunity: Post engagement level Relevance to your product Tone of the discussion Comment Templates - Set different styles for different subreddits: Technical advice for developer communities Business insights for entrepreneur groups User experience for product discussions Best Practices Start with 2-3 subreddits to test effectiveness Review and approve comments in Slack before posting Follow Reddit's 90/10 rule (90% helpful content, 10% self-promotion) Adjust the AI prompt based on what works in your communities Why Use This Saves hours of manual Reddit browsing Maintains consistent brand voice Never miss relevant conversations Team can review before engaging publicly

🛍️ Automated Product Description Generation for Adobe Commerce (Magento 2) Description This n8n template demonstrates how to automatically generate product descriptions for items in Adobe Commerce (Magento 2) that are missing one. The workflow retrieves product data, converts raw attribute values (like numeric IDs) into human-readable labels, and passes the enriched product data to an LLM (Azure OpenAI by default). The LLM generates a compelling description, which is then saved back to Magento using the API. This ensures all products have professional descriptions without manual writing effort. Use cases include: Auto-generating missing descriptions for catalog completeness. Creating consistent descriptions across large product datasets. Reducing manual workload for content managers. Tailoring descriptions for SEO and customer readability. Good to know All attribute options are resolved to human-readable labels before being sent to the LLM. The flow uses Azure OpenAI, but you can replace it with OpenAI, Anthropic, Gemini, or other LLM providers. The LLM prompt can be customised to adjust tone, length, SEO-focus, or specific brand style. Works out-of-the-box with Adobe Commerce (Magento 2) APIs, but can be adapted for other ecommerce systems. How it works Get Product from Magento Retrieves a product that has no description. Collects all product attributes. Generate Description with LLM Resolves attribute option IDs into human-readable values (e.g. color_id = 23 → "Red"). Passes the readable product attributes to an Azure OpenAI model. The LLM creates a clear, engaging product description. The prompt can be customised (e.g. SEO-optimized, short catalog text, or marketing style). Save Description in Magento Updates the product via the Magento API with the generated description. Ensures product data is enriched and visible in the webshop immediately. How to use Configure your Magento 2 API credentials in n8n. Replace the Azure OpenAI node with another provider if needed. Adjust the prompt to match your brand’s tone of voice. Run the workflow to automatically process products missing descriptions. Requirements ✅ n8n instance (self-hosted or cloud) ✅ Adobe Commerce (Magento 2) instance with API access ✅ Azure OpenAI (or other LLM provider) credentials (Optional) Prompt customisations for SEO or brand voice Customising this workflow This workflow can be adapted for: Other attributes**: Include or exclude attributes (e.g. only color & size for apparel). Different LLMs**: Swap Azure OpenAI for OpenAI, Anthropic, Gemini, or any supported n8n AI node. Prompt tuning**: Adjust instructions to generate shorter, longer, or SEO-rich descriptions. Selective updates**: Target only specific categories (e.g. electronics, fashion). Multi-language support**: Generate product descriptions in multiple languages for international shops.

This workflow automatically analyses tasks to uncover why the actual time spent exceeds the original estimates. It connects with ClickUp(Can do with any PMS like JIRA, Asana, Monday and more) and other project management tools to generate clear insights on overspending trends. Save time, improve planning accuracy, and boost team productivity with automated task time analysis with two types of reports. “Why needed extra time?”** – Reasons users requested extensions or faced blockers. “Why went over estimate?”** – Reasons the actual work exceeded the original estimation. 🔧 Workflow Overview Manual Trigger Kick off execution by clicking “Test workflow”. Fetch Relevant Tasks Calls ClickUp to retrieve all tasks in specified states (“internal review” or “in progress”) that belong to designated folders and assignees. Filter by Overrun Filters tasks to include only those where time_spent > time_estimate. Gather Details For each overrun task: Fetch time entries via ClickUp API. Fetch all comments, including threaded replies. Retain only essential task fields and reformat timestamps. Normalize and Merge Extracts and sorts comment threads into clean arrays. Sorts time entry intervals chronologically. Merges task metadata, comments, and time entries into a single payload. Pass to AI Agent Sends consolidated task data to a ChatGPT-powered node using a custom prompt that: Extracts all “extra time requests” from comments and time entries. Identifies debugging, research, clarification, or rework intervals exceeding estimates. Combines findings into two distinct checklists. Format JSON Output A final Code node parses AI output into a clean JSON array ready for conversion. Convert to File JSON result for each task is prepared for file attachment or external storage. 🧩 Key Nodes & Functions |Node Name|Responsibility| |-|-| |Get ClickUp Tasks|Retrieves tasks by filter criteria| |If task has crossed estimation|Ensures only tasks with overruns continue| |Fetch Time entries via task IDs|Retrieves detailed time intervals| |Fetch Master comments|Retrieves all comments and threads| |Split → Merge scripting nodes|Clean and normalize comments structure| |Modify Time/Task data|Trims and prepares JSON for AI processing| |OpenAI Chat Model + AI Agent|Applies a GPT-based prompt to generate two reasoned checklists in JSON format| |Convert to File|Prepares final output as a JSON file or store on Sreadsheet or Email or Excel| 🛠 Customization Tips Trigger Automation:** Integrate a scheduled node for periodic runs (e.g., daily). Filter Scope:** Adjust ClickUp filters for different task types, spaces, or statuses. AI Prompt Tuning:** Refine prompt to include severity, link references, or categorize reasons. Output Handling:* Use the JSON file in subsequent n8n nodes for notifications *(Slack, Email, Spreadsheet, Airtable, ExcelSheet, etc.) or analytics. ✅ Benefits at a Glance Automates time-overrun analysis, eliminating manual review. Extracts insights directly from tasks description, comments, and timesheets. Produces structured outputs ideal for management dashboards or retrospectives. Customizable for team-specific workflows or reporting needs. 🔐 API Credentials Needed You will required to create API key of your ClickUp Account. Follow the n8n instruction document here ++https://docs.n8n.io/integrations/builtin/credentials/clickup/++ this will guide you how you can connect your ClickUp acount with n8n workflow. 👨🏻‍💻 Need Help? Contact www.KrupalPatel.com for support and custom workflow development. Find more n8n workflow for real world use cases from here: ++https://n8n.io/creators/krupalpatel/++

Build Your First AI Agent with ChatGPT-5 Who is this for? This workflow is designed for beginners and professionals who want to build their first AI-powered assistant with n8n. It’s perfect for anyone managing online trainings, consultations, or services that require both a knowledge base and appointment scheduling. What problem is this workflow solving? Manually handling client questions, checking your availability, and confirming bookings can be time-consuming and error-prone. This workflow automates the process, ensuring quick, accurate answers and seamless scheduling directly through chat. What this workflow does Answers user questions using your knowledge base stored in Google Sheets. Checks availability in Google Calendar and proposes alternative time slots if needed. Books 1-hour appointments in Paris time only after client confirmation. Sends a professional confirmation email with all appointment details. Setup Import this workflow into your n8n instance. Connect your Google Sheets, Gmail, and Google Calendar credentials. Add your knowledge base into Google Sheets (questions, answers, policies, packs, etc.). Test the workflow using the Connected Chat Trigger node to start conversations with the AI Agent. How to customize this workflow to your needs Update the Google Sheets database with your own training packs, services, or company FAQs. Adjust the email template to reflect your branding and communication style. Modify the appointment duration if you need sessions longer or shorter than 1 hour. Add extra nodes (e.g., CRM integration) to capture leads or sync appointments with external systems. 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube

AI Interior Design Assistant: Your Digital Design Partner What This System Does This n8n workflow transforms your Telegram into a professional interior design studio powered by artificial intelligence. Send a photo of furniture or a room space, and watch as the system intelligently catalogs items, documents spaces, and generates stunning custom interior designs tailored to your vision. The Magic Behind the Scenes Smart Image Recognition When you upload a photo, the system immediately springs into action with sophisticated image analysis: Furniture Detection**: Spots individual pieces like sofas, chairs, tables, and lamps with catalog-precision accuracy Room Analysis**: Identifies complete spaces, architectural features, lighting conditions, and existing design elements Style Classification**: Determines design styles from modern minimalist to traditional classic Material Recognition**: Identifies wood types, fabric textures, metal finishes, and color palettes Intelligent Database Management The workflow maintains three interconnected databases that work like a professional design firm's catalog system: Furniture Catalog (catalog_products) Comprehensive product details including style, materials, dimensions, and compatibility Professional descriptions written for interior designers Searchable tags for quick design matching High-quality image storage for visual reference Room Documentation (rooms) Detailed space analysis including size, style, and architectural features Color palette documentation and lighting assessment Existing furniture inventory for design planning Room-specific design recommendations Design Portfolio (ai_generated_images) Archive of all AI-generated interior designs Original prompts and design descriptions Searchable by style, room type, or specific elements Ready for client presentations or further modifications AI-Powered Design Generation The system's crown jewel is its ability to create stunning interior visualizations: Contextual Understanding: Combines room characteristics with catalog products to create realistic design scenarios Professional Prompting: Generates detailed, interior-design-specific prompts that result in high-quality, commercially viable designs Style Consistency: Maintains design coherence across different elements while respecting user preferences Modification Capabilities: Can reference and modify previous designs, allowing for iterative improvements The User Experience Journey Scenario 1: Building Your Furniture Catalog Upload: Send photos of furniture pieces via Telegram Analysis: AI examines each piece, identifying style, materials, dimensions, and design era Cataloging: Items are professionally documented with searchable metadata Confirmation: Receive detailed catalog entries for each piece Scenario 2: Documenting Your Spaces Room Photos: Share images of your living spaces Space Analysis: AI assesses room size, style, lighting, and architectural features Documentation: Complete room profiles are created for design planning Inventory: Existing furniture and design elements are noted Scenario 3: Creating Custom Designs Design Request: Ask for specific interior modifications or new layouts Smart Matching: System pulls relevant items from your catalog and room data AI Generation: Gemini 2.5 Flash creates photorealistic interior designs Instant Delivery: Receive professional-quality visualizations via Telegram Scenario 4: Design Evolution Reference Previous Work: Mention earlier designs you want to modify Contextual Modification: AI understands your reference and applies new changes Enhanced Generation: Creates updated designs building on previous concepts Continuous Improvement: Iterate until the design matches your vision Technical Sophistication Multi-AI Coordination OpenAI GPT-4**: Handles complex reasoning, database operations, and user interaction Google Gemini 2.5 Flash**: Specializes in high-quality image generation with interior design expertise Intelligent Routing**: Automatically determines whether to catalog, document, or generate based on context Professional Data Structure The database schema reflects real interior design workflows: Industry-standard categorization systems Professional terminology and measurements Design compatibility matrices Style and era classifications used by actual designers Seamless Integration Telegram Interface**: No app downloads or complex interfaces - just send photos and text Cloud Storage**: All images stored in Supabase with public URLs for easy access Real-time Processing**: Immediate feedback and rapid design generation Persistent Memory**: Everything is saved and searchable for future reference Why This Matters This workflow bridges the gap between professional interior design tools and accessible consumer technology. It provides: For Design Professionals: A powerful cataloging and visualization tool that streamlines client presentations and design iteration For Homeowners: Professional-level design capability without the cost or complexity of traditional design software For Businesses: A scalable solution for furniture visualization, space planning, and customer engagement The Innovation Factor Unlike simple design apps that work with generic templates, this system: Learns your specific furniture and spaces Maintains design continuity across projects Provides professional-quality outputs Scales from single rooms to complete home designs Integrates seamlessly into your daily communication workflow The result is a design assistant that feels less like software and more like having a professional interior designer available 24/7 through your phone. Future Possibilities This foundation supports expansion into: Room dimension calculations and space optimization Integration with furniture retailers for purchase links 3D room modeling and virtual reality previews Style preference learning and automated suggestions Multi-user collaboration for design teams The workflow represents a new paradigm where AI doesn't replace human creativity but amplifies it, making professional design capabilities accessible to anyone with a smartphone and an imagination.