Airtable and Google Gemini Chat Model integration

Analyze food ingredients from Telegram photos using Gemini and Airtable 🛡️ Personal Ingredient Bodyguard Turn your Telegram bot into an intelligent food safety scanner. This workflow analyzes photos of ingredient labels sent via Telegram, extracts the text using AI, and cross-references it against your personal database of "Good" and "Bad" ingredients in Airtable. It solves the problem of manually reading tiny, complex labels for allergies or dietary restrictions. Whether you are Vegan, Halal, allergic to nuts, or just avoiding specific additives, this workflow acts as a strict, personalized bodyguard for your diet. It even features a customizable "Persona" (like a Sarcastic Bodyguard) to make safety checks fun. 🎯 Who is it for? People with specific dietary restrictions (Vegan, Gluten-free, Keto). Individuals with food allergies (Nuts, Dairy, Shellfish). Special dietary observers (Halal, Kosher). Health-conscious shoppers avoiding specific additives (e.g., E120, Aspartame). 🚀 How it works Trigger: You send a photo of a product label to your Telegram Bot. Fetch Rules: The workflow retrieves your active "Watchlist" (Ingredients to avoid/prefer) and "Persona" settings from Airtable. Vision & Logic: It uses an AI Vision model to extract text from the image (OCR) and Google Gemini to analyze the text against your strict veto rules (e.g., "Safe" only if ZERO bad items are found). Response: The bot replies instantly on Telegram with a Safe/Unsafe verdict, highlighting detected ingredients using HTML formatting. Log: The result is saved back to Airtable for your records. ⚙️ How to set up This workflow relies on a specific Airtable structure to function as the "Brain." Set up Airtable Sign up for Airtable: Click here Copy the required Base: Click here to copy the "Ingredients Brain" base Connect Airtable to n8n (5-min guide): Watch Tutorial Set up Telegram Message @BotFather on Telegram to create a new bot and get your API Token. Add your Telegram credentials in n8n. Configure AI Add your Google Gemini API credentials. Note on OCR: This template is configured to use a local LLM for OCR to save costs (via the OpenAI-compatible node). If you do not have a local model running, simply swap the "OpenAI Chat Model" node for a standard GPT-4o or Gemini Vision node. 📋 Requirements n8n** (Cloud or Self-hosted) Airtable** account (Free tier works) Telegram** account Google Gemini** API Key Local LLM* (Optional, for free OCR) OR OpenAI/Gemini* Key (for standard Cloud Vision) 🎨 How to customize Change the Persona:** Go to the "Preferences" table in Airtable to change the bot's personality (e.g., "Helpful Nutritionist") and output language. Update Ingredients:** Add or remove items in the "Watchlist" table. Mark them as "Good Stuff" or "Bad Stuff" and set Status to "Active". Adjust Sensitivity:** The AI prompt in the "AI Agent" node is set to strict "Veto" mode (Bad overrides Good). You can modify the system prompt to change this logic. ⚠️ Disclaimer This tool is for informational purposes only. Not Medical Advice: Do not rely on this for life-threatening allergies. AI Limitations: OCR can misread text, and AI can hallucinate. Verify: Always double-check the physical product label. Use at your own risk.

💅 AI Agents Generate Content & Automate Posting for Beauty Salon Social Media 📲 Who Is This For? This workflow is for beauty salons who want consistent, high‑quality social media content without writing every post manually. It also suits agencies and automation builders who manage multiple beauty brands and want a reusable, AI‑driven posting system they can adapt per client. What Problem Is This Workflow Solving? Many beauty businesses struggle to post regularly because research, copywriting, and design all take time and marketing skills. This workflow automates research, writing, image creation, and posting, so your channels stay active and relevant while you focus on clients and services. What This Workflow Does Generates short, engaging posts tailored to a beauty‑salon audience (hair, nails, skincare, make‑up, self‑care) using an AI agent. Uses Tavily Internet Search to pull up‑to‑date information and trends based on a reference link or topic. Turns each post into a detailed, photorealistic image prompt and creates a matching visual with an AI image model (for example, gpt‑image‑1 or other connected providers). Automatically sends the final text and image to Telegram, and can be extended to other social platforms from the Split Out node. How It Works Trigger the workflow Scheduled automatic generation:** Run the parent workflow on a schedule (for example, once per day at 9 AM) to publish new content regularly. Google Sheets trigger:** Generate content when a new row with a reference link or topic is added to your sheet. Use it when you manage ideas or briefs in Google Sheets and want the workflow to react as soon as a new idea appears. RSS Feed trigger:** Start the workflow when new items appear in a selected RSS feed. Ideal for turning fresh blog posts, news, or industry updates into social media content or automated summaries. Meta (Facebook/Instagram) webhook:** Use the Meta Reference trigger to fire the workflow on incoming webhooks from Meta (for example, new comments, messages, or events). Helpful when you want to auto‑respond, log activity, or generate follow‑up content from Meta activity. Airtable trigger:** Start the workflow when records in a selected Airtable base/table change (for example, a new idea, brief, or status update), so your posts react instantly to updates in your Airtable content board. Postgres trigger:** Fire the workflow when new rows are inserted or existing rows are updated in a connected PostgreSQL table, letting you drive content generation from events in your app database or Supabase‑style back end. Manual start:* Hit Execute workflow* whenever you want to spin up a batch of posts on demand, test new prompt settings, or debug the flow step by step. Research and generate copy The GENERATE TEXT agent calls Tavily to gather fresh information on the topic. It writes a post under 1024 characters with a hook, practical tips, relevant hashtags, and a closing line with your salon address and contact. Create the visual The GENERATE PROMPT agent converts the post into a single, clear description of the scene (client, service, salon interior, lighting, mood) with a strict “no text on image” rule. An image model such as gpt‑image‑1 or one of the HTTP image APIs renders a matching beauty visual. Distribute the content The Split Out node fans out the result so Telegram receives a photo post with the generated caption. Additional social or content nodes (for example Facebook, LinkedIn, X, template tools) can be wired after this step for multi‑channel posting. How to Customize This Workflow to Your Needs Brand voice** Edit the system message in the GENERATE TEXT node to adjust tone (luxury, friendly, clinical, playful), language, services, and city. Update the final address and phone line to match your salon details. Topics and triggers** Point the Google Sheets Trigger to your own document ID, sheet, and columns for ideas, links, or campaign themes. Use the Schedule Trigger for fully automatic posting or rely on the Manual Trigger for controlled, batch generation sessions. Models and providers** Swap GPT‑5 llm and the default image model for alternatives such as Mistral, Gemini, Anthropic, DeepSeek, or custom HTTP image APIs by enabling the corresponding nodes and adding credentials. Channels and outputs** Connect or remove social nodes after Split Out depending on which platforms you actively use. Add extra processing steps (for example resizing images or adding UTM parameters) before each channel if needed. Visual style** Tweak the GENERATE PROMPT instructions to control composition (close‑up vs. full‑body), color palette, lighting, and overall salon aesthetic, while keeping the constraint of no text or logos in the image.

Who Is This For? This workflow is designed for marketers, content creators, agencies, and solo founders who want to publish long‑form posts with visuals on autopilot using n8n and AI agents. ​ Whether you run a blog, SaaS, personal brand, newsletter, or client accounts, this tool helps you keep a consistent content pipeline without manually writing every article, creating images, and posting to each platform one by one. ​ ​ 💪🏼 While the template is wired around classic blog + social media distribution, the underlying logic is universal. You can easily adapt it to any niche by editing prompts, swapping models, and re‑wiring nodes. You can plug in any LLM you like, from ChatGPT to Claude, Gemini, Mistral, DeepSeek, OpenRouter, or even local models through Ollama. ​ What Problem Is This Workflow Solving? 🤯 Most teams waste hours on the same repetitive loop: research a topic, gather links, write a blog post, craft social captions, generate visuals, upload everything to multiple platforms, and archive assets. ​ ​ 💎 This workflow solves that by automating the full content chain—from research and blog‑post generation to image creation, publishing across channels, and logging everything in your content database—so your feeds stay active while you focus on strategy, not busywork. ​ What This Workflow Does ✨ Generates in‑depth blog posts tailored to your topic and target audience, enriched with fresh references from the web via Tavily/SerpAPI search tools. ​ ✨ Creates an image prompt and title from the article, generates the visual with OpenAI Images (gpt-image-1), and converts it into a ready‑to‑use image file. ​ ✨ Automatically publishes content to your connected platforms (WordPress for blog posts, Telegram, X/Twitter, Facebook, LinkedIn) while saving images to Google Drive and logging each publication in Google Sheets for tracking. ​ How It Works? Surprisingly simple ☺️ The workflow is triggered by another n8n workflow or by one of several triggers (Facebook, RSS, Google Sheets, Airtable, Postgres) that pass in the blogTopic, targetAudience, and Telegram chatID. ​ ​ The Blog Post Agent (LLM with access to Tavily/SerpAPI) researches the topic, writes a structured article for the specified audience, and sends its output to the Image Prompt Agent, which turns the content into a visual prompt and title. ​ 🎯 The end result: you provide a topic, run the workflow, and receive a complete blog post, matching image, and ready‑made social posts shipped directly to your channels and archives—no manual copy‑paste. ​ How to Customize This Workflow to Your Needs 🎨 Switch AI models and fine‑tune prompts so the agent can handle your exact formats: tutorials, case studies, listicles, product updates, thought‑leadership pieces, or campaign landing posts. 🔍 Refine research sources inside Tavily/SerpAPI to prioritize the domains, blogs, and docs your audience trusts, keeping posts accurate and up to date. ⏰ Adjust posting cadence and schedules to align with peak engagement for your audience, mixing automated slots with manual “launch” runs for special announcements. 📱 Expand or trim channels as needed: keep just WordPress + LinkedIn, add Telegram as a content feed, or plug the workflow into additional automations like email campaigns or RSS feeds. 📊 Use Google Sheets as your content hub to store ideas, angles, CTAs, references, and performance notes so you can double‑down on topics and formats that perform best. 🎬 Swap images for video by replacing the image generation node with video tools (for example, Runway‑style APIs) if your strategy is video‑first while keeping the same prompt pipeline. 💾 Build a reusable prompt library in Sheets, Notion, or Airtable so you can rotate proven prompt patterns each month and keep quality high without reinventing the wheel. 🤖 The system will continuously generate blog posts, visuals, and social updates and publish them across your selected platforms while archiving everything in Drive and Sheets—keeping your brand visible, consistent, and professional with minimal ongoing effort.

How it works Automates systematic literature review by downloading papers from Google Drive, extracting text, and evaluating them against strict inclusion/exclusion criteria using LLM agents Routes included papers to Qdrant vector stores with Gemini embeddings for semantic search, and excluded papers to a separate folder Logs all decisions to Airtable with PRISMA-compliant justification for complete audit trails Set up steps Connect Google Drive credentials to access your paper folder Configure Airtable base and table for decision logging Add OpenAI (GPT-4) and Google Gemini API credentials for LLM evaluation and embeddings Set up Qdrant instances for vector storage (supports up to 3 collections) Keep detailed descriptions of your inclusion/exclusion criteria in the sticky notes inside your workflow

This n8n template from Intuz provides a complete end-to-end content factory to automate the entire lifecycle of creating and publishing AI-driven videos. It transforms a single text prompt into a fully scripted, visually rich video with AI-generated images and voiceovers, then distributes it across multiple social media platforms. Who's this workflow for? Content Creators & YouTubers Social Media Managers & Agencies Digital Marketers & Entrepreneurs Brands looking to scale video content production Objective Generate viral video scripts with Gemini AI (via LangChain). Break scripts into structured scenes(hooks, retention, CTA). Create image prompts and high-quality background visuals automatically. Store all scenes, prompts, images, and metadata into Airtable. Handle file formatting, uploads, and naming automatically. Add error handling and retry logic for smooth execution. Uploading into Social Media platforms. How it works AI Script Generation: The workflow starts with a single command. A powerful Google Gemini AI model, acting as a "Content Brain," generates a complete, viral video script with a title, description, and multiple scenes. Content Management in Airtable: The entire script is broken down and saved systematically into an Airtable base, which acts as the central Content Management System (CMS) for the video production pipeline. AI Image Generation: The workflow loops through each scene in Airtable. It uses an AI agent to enhance the image prompts and sends them to an image generation API (like Pollinations.ai) to create a unique, high-quality image for each scene. These images are then automatically uploaded back into Airtable. Automated Video Rendering: Once all images are ready, the workflow gathers the script text and the corresponding image URLs from Airtable and sends them to Creatomate. Creatomate uses a pre-defined template to assemble the final video, complete with AI-generated voiceovers for each scene. Multi-Platform Publishing: After a brief wait for the video to render, the workflow retrieves the final video file and automatically publishes it across your connected social media channels, including YouTube and Instagram. Key Requirements to Use This Template Before you start, please ensure you have the following accounts and assets ready: n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow relies on the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed on your instance. AI & Video Accounts: Google Gemini AI Account: A Google Cloud account with the Vertex AI API enabled and an API Key. Creatomate Account: It's platform to generate videos. An account with Creatomate for video rendering, and your API key and a pre-designed video template ID. Content & Social Media Accounts: Airtable Account: An Airtable base set up to manage the video content. Using the complementary Airtable template is highly recommended. YouTube Account: A YouTube channel with API access enabled via Google Cloud Console. Upload-Post.com Account: An account for posting to other platforms like Instagram. Workflow Steps 1.▶️ Trigger (Manual/Auto) Start workflow manually or via schedule. 2.🧠 Content Brain (Gemini + LangChain) Role-trained viral strategist prompt. Generates 6 scene scripts with: Hook → Retention → Value → CTA. Follows viral content rules (engagement triggers, curiosity gaps, shareable moments). 3.📑 Structured Output Parser Enforces JSON schema: video_id video_title description scenes[] → scene_number, text, image_prompt 4.📄 Airtable – Store Scenes Each scene stored with: Video ID, Title, Description Scene Number & Text Image Prompt & Generated Image link 5.🤖 AI Agent – Image Prompt Creator Transforms scene text →optimized image prompts using structured rules. 6.🎨 Pollination AI – Image Generation Generates vertical 9:16 visuals with parameters: Model: flux Resolution: 1080x1920 Steps: 12 Guidance Scale: 3.5 Safety Checker: Enabled Options: seed=42, nologo=true 7.📂 File Handling & Conversion Assigns filenames automatically (e.g., images_001.png). Converts binary image → base64 for Airtable storage. 8.📤 Airtable Upload – Store Images Attaches generated visuals directly into Generated Image field. 9.⚡ Switch & Error Handling Branches for: ✅ Success → continue ❌ Failed → stop with error message ⏳ Processing → wait/retry 10.Social Media Upload In YouTube via YouTube API from official documentation In Instagram Via Upload Post API Setup Instructions AI Configuration: In the Google Gemini Chat Model nodes, connect your Google Gemini API account. In the Content Brain node, you can customize the core prompt to change the video's niche, style, or topic. Airtable Setup (Crucial): Connect your Airtable account in the Airtable nodes. Set up your Airtable base using the provided template or ensure your base has identical table and field names. Update the Base ID and Table IDs in the Airtable nodes. Airtable Schema: Video Rendering Setup (Creatomate): In the Video Rendering - Creatomate node, add your Creatomate API key to the header authorization. In the Template for Creatomate node, replace the template_id with the ID of your own video template from your Creatomate account. Social Media Connections: In the Upload on YouTube node, connect your YouTube account via OAuth2. In the Upload on Instagram node, replace the API key in the header authorization with your key from Upload-Post.com. Execute the Workflow: Click "Execute workflow" to kick off your automated video content factory. Connect with us Website: https://www.intuz.com/n8n-workflow-automation-templates Email: [email protected] LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

Workflow Overview This workflow automatically fetches the latest "Ask HN: Who is hiring?" posts from Hacker News, extracts individual job listings, cleans the raw text, converts them into structured job listings using Google Gemini AI, and saves them into Airtable. Components It’s a full end-to-end automation system combining: Algolia API** for HN data Text cleaning** Gemini AI (via LangChain)** for parsing job descriptions Structured JSON extraction** Airtable integration** to store the final data 🎯 Use Cases Automatically build a job board from HN posts Track startup hiring trends Feed remote job alerts into a CRM or Slack Enrich a hiring intelligence database 🔧 Nodes & Services Used HTTP Request (Algolia + Firebase API) SplitOut, Set, Filter, Function, Limit Google Gemini (via LangChain integration) Output Parser Structured Airtable (API token required) 📌 Credentials Required Google Gemini (PaLM/Gemini API) Airtable Personal Access Token Algolia Application ID & API Key (via Header Auth) 📦 Tags hacker-news, jobs, airtable, ai, gemini, automation, hn, langchain, workflow Screenshots

Who this is for? Indeed Data Scraper & Summarization with Airtable, Bright Data and Google Gemini is an automated workflow that extracts company profile information from Indeed using Bright Data Web Unlocker, transforms the data using Google Gemini's LLM, and forward the transformed response with the summary to a specified webhook for downstream use. This workflow is tailored for: Recruiters and HR teams who want quick summaries of companies listed on Indeed. Market researchers and analysts needing structured insights into businesses. Founders, investors, and consultants scouting potential competitors, partners, or clients. No-code enthusiasts looking to automate data extraction and enrichment pipelines without manual scraping or parsing. What problem is this workflow solving? Manually gathering structured information about companies on Indeed is time-consuming and inconsistent. Pages vary in structure, and extracting clean, digestible summaries can require technical scraping expertise. This workflow automates: Extracting company data from Indeed reliably using Bright Data Web Unlocker. Cleaning and summarizing the extracted content using Google Gemini LLM. Storing structured insights directly into Airtable for easy access and further workflows. Eliminates manual research, saves hours, and produces AI-enhanced, easily searchable records. What this workflow does Triggers on-demand. Pulls company page URLs from Airtable. Scrapes content from each Indeed company profile using Bright Data Web Unlocker. Sends the raw HTML to Google Gemini for extraction and summarization. Sends the summarized data to other platforms via a Webhook notification mechanism. 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 for Bright Data. The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). In n8n, configure the Airtable Personal Access Token account under Credentials. Update the Webhook Notifier with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a company or a market researcher, entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Extend the scraper**: Modify Bright Data targets to pull job listings, salaries, or employee reviews via the Airtable data source. Customize the summary prompt**: Ask Gemini to extract different attributes hiring trends, practices etc. Routing the output to different destinations**: Send summaries or transformed response to Google Sheets, Airtable, or CRMs like HubSpot or Salesforce etc.

Fully Automated AI Email System for n8n: Triage, Summarize & Alert—Never Check Your Inbox Again! Fully Automated Email Intelligence: Triage, Summarize, Escalate & Alert—Never Check Your Inbox Again 🚀 Overview Turn every minute you waste in your inbox into revenue‑generating focus time. This is more than a workflow—it’s a profit engine disguised as an email assistant. ⚙️ Eliminate 90 % of inbox noise with AI triage and smart labeling. 🚨 Instantly surface high‑value leads & crises via Telegram push alerts—before they cost you. 📰 Digest newsletters in 60 seconds with bite‑size AI briefs that keep you ahead of the curve. 🤖 Hand off replies, snoozes, and archiving to a tireless autonomous agent that never slips. Set‑up takes 10 minutes. The payoff starts within the first hour—hours reclaimed, opportunities captured, and the calm certainty your inbox is handled perfectly, 24/7. 🎯 Who's It For? Startup Founders & CEOs – Stop wasting hours on inbox cleanup. Automatically surface leads, triage support, and escalate ops issues while you focus on growth. Agencies & Consultants – Instantly prioritize high-value client messages, flag urgent ops threads, and never drop the ball on critical communication. Busy Professionals & Teams – Reclaim 5–10 hours weekly by letting AI handle noise, flag what matters, and summarize newsletters into actionable insights. No-Code Builders & AI Engineers – Plug in, customize, and ship production-ready inbox automation in minutes—no training required. Remote Operators & Virtual Assistants – Delegate inbox management confidently with a system that flags what’s important and handles the rest. 📌 High‑Impact Results What You’re Dealing With → What This System Solves Instantly Inbox Clutter & Constant Noise → 90% Noise Reduction Trivial, low-value messages are automatically triaged and labeled—only high-value threads stay in your spotlight. Missing Critical Emails → Real-Time Telegram Alerts Get instantly notified the moment a client, lead, or ops-critical email lands. Zero lag. Zero drop. Manual Reply Fatigue → AI-Generated Drafts in Seconds Fully contextual, brand-aligned replies ready at a click—cut response time from minutes to seconds. Newsletter Overload → Actionable 60-Second Summaries Dense newsletters converted into digestible, decision-ready highlights. Save hours while staying sharp. Information Chaos → Fully Structured Inbox Intelligence From raw email to labeled insights to escalated alerts—your inbox becomes an automated decision support system. This system doesn’t just "help"—it replaces hours of work per week, prevents costly misses, and ensures you never drown in emails again. ⚙️ Powerful Features 📥 AI Email Triage – Classifies and sorts emails using GPT/Gemini, labeling by intent and urgency. 📰 Newsletter Summarizer – Extracts concise, actionable insights from newsletters into structured summaries. 🚨 Real-Time Priority Alerts – Instantly escalates mission-critical emails via Telegram. 🤖 Autonomous Inbox Agent – Proactively manages email actions: replies, drafts, archives, and thread labeling. 🧠 Persistent Context Memory – Remembers senders, conversation history, and adjusts responses accordingly. 🏅 Why Choose This Solution? Fully Self-Hosted & Secure – Keep full control of your data and privacy. No external storage, no SaaS lock-in—just your infrastructure, your rules. Production-Grade Reliability – Built by a Lead Software Engineer. Tested, trusted, and optimized for uptime by myself. AI-Native Workflow Engine – Smart, adaptive, and deeply embedded in your processes. Automates with context, learns with use, and gets smarter over time. 💰 Pricing Limited Time Launch Price: $29 (One-time payment) 🎯 Lifetime access—pay once, save time forever. ⏱️ Designed to reclaim 5–10 hours per week per inbox. 🚨 One missed priority email could cost more—this system prevents that. ⚡ Launch offer pricing will increase SOON!—lock in early. 📦 What's Included? ✅ Fully documented and annotated n8n workflow (ready-to-import JSON) 📂 Gmail labeling system (production-ready taxonomy) 📲 Telegram integration and alert configuration 🛠 Customizable AI prompt templates for Gemini/GPT 🧠 Custom prompt templates for GPT & Gemini ⚙️ Autonomous email categorization & filtering 📰 Newsletter summarizer with structured JSON output 🤖 Optional AI agent for full inbox management tasks 🚀 Quick Start Setup Import the full workflow into your self-hosted n8n environment. Connect your Gmail, Telegram, and preferred LLMs (OpenAI or Gemini). Deploy Gmail labels using the included taxonomy—ensures proper triage and filtering. Trigger test alerts from real email data to verify AI classification and Telegram escalation. Go live—start receiving summarized insights, escalations, and triaged inbox updates within minutes. ❓ FAQ Q: What kind of ROI can I expect? A: On average, users reclaim 5–10 hours per week per inbox by eliminating low-priority noise, surfacing urgent emails instantly, and automating replies and summaries. For a business leader or agency, that’s hundreds of dollars in time savings weekly—and zero dropped balls. Q: Can it scale for my team? A: Absolutely. It’s architected with modular nodes and reusable components so you can rapidly duplicate, extend, or adapt it across teams, departments, and workflows. Whether you’re a solo founder or managing 20+ inboxes, this system grows with you—without code rewrites. Q: Is my data secure? A: Absolutely!. This system runs entirely in your self-hosted n8n environment, so your data never leaves your control. External LLMs (like OpenAI or Gemini) are only used when needed and receive minimal, context-limited input. You control all API keys and endpoints. No data is stored externally unless you configure it. Made with ❤️ by Bluegrass Digital Advantage

This workflow is designed to generate prompts for AI agents and store them in Airtable. It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable. Setup Instructions Prerequisites AI model eg Gemini, openAI etc** Airtable base and table or other storage tool** Step-by-Step Guide Clone the Workflow Copy the provided workflow JSON and import it into your n8n instance. Configure Credentials Set up the Google Gemini(PaLM) API account credentials. Set up the Airtable Personal Access Token account credentials. Map Airtable Base and Table Create a copy of the Prompt Library in Airtable. Map the Airtable base and table in the Airtable node. Customize Prompt Template Edit the 'Create prompt' node to customize the prompt template as needed. Configuration Options Prompt Template:** Customize the prompt template in the 'Create prompt' node to fit your specific use case. Airtable Mapping:** Ensure the Airtable base and table are correctly mapped in the Airtable node. Running and Troubleshooting Running the Workflow Trigger the Workflow: Send a chat message to trigger the workflow. Monitor Execution: Use the n8n interface to monitor the workflow execution. Check Completion: Verify that the prompt is stored in Airtable and check the chat interface for the result. Troubleshooting Tips API Issues:** Ensure that the APIs and Airtable credentials are correctly configured. Data Mapping:** Verify that the Airtable base and table are correctly mapped. Prompt Template:** Check the prompt template for any errors or inconsistencies. Use Case Examples This workflow is particularly useful in scenarios where you want to automate the generation and management of AI agent prompts. Here are some examples: Rapid Prototyping of AI Agents: Quickly generate and test different prompts for AI agents in various applications. Content Creation:** Generate prompts for AI models that create blog posts, articles, or social media content. Customer Service Automation:** Develop prompts for AI-powered chatbots to handle customer inquiries and support requests. Educational Tools:** Create prompts for AI tutors or learning assistants. Industries/Professionals: Software Development:** Developers building AI-powered applications. Marketing:** Marketers automating content creation and social media management. Customer Service:** Customer service managers implementing AI-driven chatbots. Education:** Educators creating AI-based learning tools. Practical Value: Time Savings:** Automates the prompt generation process, saving significant time and effort. Improved Prompt Quality:** Leverages Google Gemini and structured prompt engineering principles to generate more effective prompts. Centralized Prompt Management:** Stores prompts in Airtable for easy access, organization, and reuse. Running and Troubleshooting Running the Workflow:** Activate the workflow in n8n. Send a chat message to the webhook URL configured in the "When chat message received" node. Monitor the workflow execution in the n8n editor. Monitoring Execution:** Check the execution log in n8n to see the data flowing through each node and identify any errors. Checking for Successful Completion:** Verify that a new record is created in your Airtable base with the generated prompt, name, and category. Confirm that the "Return results" node sends back confirmation of the prompt in the chat interface. Troubleshooting Tips:** Error:** 400: Bad Request in the Google Gemini nodes: Cause:** Invalid API key or insufficient permissions. Solution:** Double-check your Google Gemini API key and ensure that the API is enabled for your project. Error:** Airtable node fails to create a record: Cause:** Invalid Airtable credentials, incorrect Base ID or Table ID, or mismatched column names. Solution:** Verify your Airtable API key, Base ID, Table ID, and column names. Ensure that the data types in n8n match the data types in your Airtable columns. Follow me on Linkedin for more

🏠 AI Real Estate Lead Qualifier — Typeform to Airtable with Smart Email Routing Automatically qualify property leads, score them with AI, save to Airtable, and send personalised emails — all in seconds. 📖 Description Every time a prospect submits your Typeform property inquiry, this workflow kicks in automatically. It extracts their details, runs them through an AI lead scoring engine, saves the record to Airtable, and sends a personalised email — a priority response for hot leads, a nurture email for everyone else. No manual review. No missed leads. No delayed follow-ups. This is built for real estate agencies, leasing companies, and property managers who receive inquiries through Typeform and want instant, intelligent responses without hiring extra staff. ✨ Key Features Instant lead capture** — triggers the moment Typeform receives a submission AI lead scoring** — Google Gemini classifies every lead as High, Medium, or Low automatically Smart email routing** — High leads get a priority response, others get a nurture sequence Airtable CRM sync** — every lead saved with full details + AI assessment Robust AI parsing** — 4-layer fallback system ensures AI output is always usable Personalised emails** — name, property type, location, budget pulled into every email automatically No-code maintenance** — update scoring rules in the prompt, email copy in the nodes 🔄 How It Works Prospect submits Typeform inquiry ↓ Webhook receives the form payload ↓ Extract Typeform Fields → name, email, phone, property type → purpose, location, budget, requirements ↓ AI Lead Qualifier (Google Gemini) → lead_score: High / Medium / Low → intent, timeline, notes ↓ Parse AI Output (4-layer fallback) ↓ Save to Airtable CRM ↓ High Lead? (IF check) ✅ YES → Priority Email (contact within 2 hours) ❌ NO → Nurture Email (contact within 1-2 days) 🤖 AI Lead Scoring Rules The AI automatically classifies leads based on these criteria: | Score | Criteria | | :--- | :--- | | 🔴 High | Has budget + specific location + clear purpose (investment or near-term buying) | | 🟡 Medium | Partial information — needs follow-up to qualify further | | 🟢 Low | Vague inquiry, missing budget or location, early exploration | The AI also extracts: Intent** — what the lead is trying to achieve Timeline** — how urgently they need a property Notes** — assessment summary for your sales team 📧 Email Templates High Lead Email Subject: 🏠 [Name], we have properties matching your needs! Dark blue header — premium feel Full inquiry summary (property, purpose, location, budget, timeline) AI assessment notes included Promise: senior agent contacts within 2 hours Nurture Email (Medium / Low) Subject: Thanks for reaching out, [Name]! Grey header — warm and professional Inquiry summary (property, location, budget) Preparation tips while they wait Promise: contact within 1-2 business days 🛠 Setup Requirements Typeform Setup Create a Typeform with these fields and note their field ref IDs from the Typeform API: | Field | Type | Required | | :--- | :--- | :---: | | Full Name | Short text | ✅ | | Phone Number | Phone | ✅ | | Email Address | Email | ✅ | | Property Type | Multiple choice | ✅ | | Purpose | Multiple choice | ✅ | | Preferred Location | Short text | ✅ | | Budget Range | Multiple choice | ✅ | | Requirements | Long text | ✅ | | Consent | Yes/No | Optional | Connect Typeform webhook: Typeform Dashboard → Connect → Webhooks URL: your n8n webhook URL (Production URL from the Webhook node) Method: POST Update Field Refs In the Extract Typeform Fields Code node, update the REF_* constants to match your actual Typeform field reference IDs: const REF_NAME = 'your-field-ref-here'; const REF_EMAIL = 'your-field-ref-here'; const REF_PHONE = 'your-field-ref-here'; // ... etc Find your field refs from the Typeform API or by logging a test webhook payload. Airtable Setup Create an Airtable base with a table containing these fields: | Field Name | Field Type | | :--- | :--- | | Full Name | Single line text | | Email Address | Email | | Mobile Phone Number | Phone | | Property Type | Single line text | | Purpose | Single line text | | Preferred Location | Single line text | | Budget Range | Single line text | | Requirements | Long text | | Submit Date | Single line text | | Lead Score | Single line text | | Intent | Single line text | | Timeline | Single line text | | Notes | Long text | Update the Save to Airtable node with your Base ID and Table ID. Credentials Required | Credential | Used for | Free? | | :--- | :--- | :--- | | Google Gemini (PaLM) API | AI lead scoring | Free tier available | | Airtable Personal Access Token | CRM save | Free | | SMTP | Sending emails | Depends on provider | Email Configuration In both email nodes, update: fromEmail — your sending address SMTP credential — your email provider details Recommended SMTP providers for testing: Mailtrap (sandbox), Gmail, SendGrid ⚙️ Workflow Nodes | Node | Type | Purpose | | :--- | :--- | :--- | | Webhook | Webhook | Receives Typeform POST payload | | Extract Typeform Fields | Code | Parses answers by field ref ID | | AI Lead Qualifier | AI Agent | Scores lead using Gemini | | Google Gemini Chat Model | LLM | AI model for scoring | | Parse AI Output | Code | Extracts JSON with 4-layer fallback | | Save to Airtable | Airtable | Creates CRM record | | High Lead? | IF | Routes by lead score | | Priority Email | Email Send | Sends to High leads | | Nurture Email | Email Send | Sends to Medium/Low leads | 🔧 Customisation Change scoring criteria: Edit the prompt in the AI Lead Qualifier node. Add your own rules — e.g. score higher if budget exceeds a threshold, or if the purpose is investment. Add more email tiers: Add a third IF branch for Low leads with a different nurture sequence, or add a Slack/WhatsApp alert for High leads. Use a different form: The Extract Typeform Fields node uses Typeform's field.ref system. Replace it with a Google Forms or Jotform parser by adjusting how you read the incoming webhook body. Change the AI model: Replace the Google Gemini node with Claude, OpenAI, or any other LLM Chat Model node — no other changes needed. Add lead deduplication: Before saving to Airtable, add a search step to check if the email already exists and skip or update instead of creating a duplicate. 🛡 Robustness Features The Parse AI Output node uses a 4-layer fallback to ensure the workflow never breaks due to AI formatting issues: Direct JSON parse — if Gemini returns clean JSON Strip markdown fences — if Gemini wraps in Regex JSON extraction — if there's extra text around the JSON Field-by-field regex — if JSON is malformed, extracts each field individually Default fallback — if all else fails, sets lead_score: Medium This means the workflow continues and saves the record even if the AI returns unexpected output. 📊 Sample Airtable Record Full Name: Sarah Johnson Email Address: [email protected] Mobile Phone: +91 9876543210 Property Type: 2BHK Apartment Purpose: Investment Preferred Location: Bandra, Mumbai Budget Range: ₹80L - ₹1.2Cr Requirements: Parking, gym, sea view Submit Date: 2026-03-18T10:30:00Z Lead Score: High Intent: Serious buyer looking for investment property with strong rental yield Timeline: Within 3 months Notes: High-intent lead with clear budget and location. Has specific amenity requirements. Recommend immediate callback. 📦 Requirements Summary n8n (cloud or self-hosted) Typeform account (any paid plan for webhooks) Airtable account (free tier works) Google AI Studio account for Gemini API key (free tier available) SMTP email account 💡 Enhancement Ideas WhatsApp alert** — send instant WhatsApp to sales team for every High lead via Twilio Calendar booking link** — include a Calendly link in the High lead email Lead follow-up reminder** — add a Wait node + reminder email if no reply in 48 hours Slack notification** — ping your team channel instantly for High leads Lead scoring dashboard** — connect Airtable to a dashboard tool for weekly reports Built with n8n · Google Gemini AI · Typeform · Airtable · SMTP

This n8n workflow automates review collection, analysis, and reporting by scraping review links from Airtable, extracting structured review data, storing it in Google Sheets, and generating AI-powered sentiment insights using Google Gemini. Use Cases Automated Review Tracking: Continuously fetch and process customer reviews without manual effort. Sentiment Analysis & Insights: Identify overall sentiment, common praise, complaints, and improvement areas using AI. Centralized Review Storage: Store all extracted reviews (date, text, rating) in Google Sheets for easy access and reporting. Scheduled Reporting: Receive summarized review insights via email on a defined schedule. Good to Know The workflow runs on a daily schedule to process new review links stored in Airtable. Reviews are processed in batches to avoid rate limits and improve stability. Google Gemini is used for intelligent review extraction and sentiment analysis, which may incur API costs. Gemini models can be geo-restricted; a “model not found” error may indicate regional unavailability. How it Works Review Collection & Storage Airtable Search: The workflow starts by searching Airtable for records that contain review links. Decodo Scraper: Review links are processed to extract raw review content from external sources. Loop Over Items: Reviews are handled in controlled batches for reliable processing. AI Review Analyzer: Google Gemini extracts structured data such as review date, text, and rating. Google Sheets Append: Each extracted review is saved as a new row in Google Sheets. AI Review Analysis & Reporting Scheduled Trigger: On a defined interval, the workflow fetches all stored reviews from Google Sheets. Data Structuring Code: Reviews are transformed into a clean, structured JSON format for analysis. AI Agent (Google Gemini): The AI analyzes all reviews to determine sentiment, key positives, common complaints, and improvement suggestions. Email Notification: A summarized review analysis is sent via Gmail. How to Use Airtable Credentials: Connect your Airtable account and ensure review links are stored in the specified table. Google Sheets Credentials: Set up Google Sheets OAuth2 to store and retrieve review data. Google Gemini Credentials: Configure your Google Gemini API key for AI-powered extraction and analysis. Gmail Credentials: Connect a Gmail account to receive automated review summaries. Activate Workflow: Enable the workflow to start automated review monitoring and reporting. Requirements n8n instance (self-hosted or cloud) Airtable base containing review links Google Sheets document for storing reviews Google Gemini API key Gmail account for sending reports

This n8n workflow automates job discovery by scanning company career pages, extracting open positions using AI, filtering them by department, and sending real-time alerts via Slack and email. It is ideal for monitoring targeted job roles (such as Engineering) across multiple companies without manual checking. Use Cases Targeted Job Monitoring: Automatically track new job postings for a specific department or role. Faster Job Alerts: Receive instant Slack and email notifications when relevant positions are found. Multi-Company Career Tracking: Monitor multiple company career pages from a single Airtable base. Reduced Noise: Filter out irrelevant roles and avoid empty or misleading notifications. Good to Know The workflow runs on a schedule and processes career pages stored in Airtable. Jobs are processed in batches with a delay node to avoid rate limits or scraping issues. Google Gemini is used for intelligent job extraction and filtering, which may incur API costs. If no relevant jobs are found, the workflow safely returns “No matching positions found” to prevent false alerts. Some Gemini models may be geo-restricted depending on your region. How it Works Step 1: Job Source & Scheduling A Schedule Trigger starts the workflow and defines the job category to monitor (e.g., Engineering). Airtable is queried to fetch all company career page URLs. Step 2: Scraping & Extraction Each career page is scraped using Decodo. Google Gemini analyzes the raw page content and extracts job titles with application URLs while ignoring navigation and non-job content. Step 3: Data Cleaning & Structuring A JavaScript code node cleans the AI output, removes noise (e.g., “No open positions”), and converts results into structured job items. Step 4: AI-Based Filtering A second AI Agent compares extracted jobs against the target department and keeps only relevant roles. Step 5: Notifications Matching jobs are sent instantly to Slack and email. How to Use Airtable Credentials: Connect Airtable and store career page URLs in the table. Google Gemini Credentials: Add your Gemini API key for AI extraction and filtering. Slack Credentials: Select a user or channel to receive job alerts. Gmail Credentials: Configure Gmail to receive job notification emails. Schedule Setup: Adjust the trigger interval based on how often you want job checks. Activate Workflow: Enable the workflow to start automated job monitoring. Requirements n8n instance (self-hosted or cloud) Airtable base with company career page URLs Google Gemini API key Slack workspace Gmail account for email notifications

Description This workflow acts as an autonomous Tier 2 Customer Support Agent. It doesn't just answer questions; it manages the entire lifecycle of a support ticket—from triage to resolution with Guardrails to deal with prompt injections, PII information blocking, etc. enabling such threats are blocked and logged in Airtable. Unlike standard auto-responders, this system uses a "Master Orchestrator" architecture to coordinate specialized sub-agents. It creates a safe, human-like support experience by combining RAG (Knowledge Base retrieval) with a safety-first state machine. How it works The workflow operates on a strict "Hub and Spoke" model managed by a Master Orchestrator: Security Guardrails (The Gatekeeper) Before the AI even sees the message, a hard-coded security layer scans for Prompt Injection attacks, Profanity, and PII. If a threat is detected, the workflow locks down, logs the incident to Airtable, and stops execution immediately. Orchestration & Triage Once the message passes safety checks, the Master Orchestrator takes over. Its first action is to call the Ticket Analyser Agent. Analysis & Scoring The Ticket Analyser classifies the issue (e.g., "Technical," "Billing") and scores the customer's sentiment. It returns a priority_score to the Master Orchestrator. The Decision Logic (Circuit Breaker) The Master Orchestrator evaluates the score: Escalation: If the customer is "Furious" or the score is high, it bypasses AI drafting and immediately alerts a human manager via Slack. Resolution Path: If the request is standard, it proceeds to the next steps. Knowledge Retrieval (RAG) The Orchestrator calls the Knowledge Worker Agent. This agent searches your Supabase vector store to find specific, verified company policies or troubleshooting steps relevant to the user's issue. Resolution Drafting Armed with the analysis and the retrieved facts, the Orchestrator calls the Resolution Agent. This agent synthesizes a polite, professional email draft. Final Execution The Master Orchestrator reviews the final draft and sends the email via Gmail. Set up This is multi-agent system. Please follow these steps to configure the environment: ⚠️ IMPORTANT: This template contains the Main Orchestrator AND the Sub-Agents in a single view. You must separate them for the system to function: Separate the Agents: Copy the nodes for each sub-agent (Ticket Analyser, Knowledge Worker, Resolution Agent) into their own new workflows. Link the Tools: In the Main Orchestrator workflow, open the "Call [Agent Name]" tool nodes and update the Workflow ID to point to the new workflows you just created. Configure Credentials: You will need credentials for Gmail (or your preferred email provider), Slack, Airtable, Supabase (for the vector store), and Google Gemini (or OpenAI). Initialize the Knowledge Base: Open the "One time Document Loader" section in the workflow. Upload your policy document (PDF/Text) to the "Upload your file here" node. Run this branch once to vectorize your documents into Supabase. Setup Airtable: Create a simple table with columns for Sender Email, Incident Type, and Flagged Content to log security threats caught by the guardrails. Customize the Trigger: Update the Gmail Trigger node to watch for your specific support alias (e.g., [email protected]) and ensure it only picks up "Unread" emails. Adjust the Escalation Sensitivity: In the Orchestrator Agent node, you can tweak the "Phase 2" logic to change what triggers a human hand-off (currently set to priority_score >= 0.9). Good to go!

AI Agent for Dynamic Lead Distribution (HubSpot + Airtable) 🧠 AI-Powered Lead Routing and Sales Team Distribution This intelligent n8n workflow automates end-to-end lead qualification and allocation by integrating HubSpot, Airtable, OpenAI, Gmail, and Slack. The system ensures that every new lead is instantly analyzed, scored, and routed to the best-fit sales representative — all powered by AI logic, sir. 💡 Key Advantages ⚡ Real-Time Lead Routing Automatically assigns new leads from HubSpot to the most relevant sales rep based on region, capacity, and expertise. 🧠 AI Qualification Engine An OpenAI-powered Agent evaluates the lead’s industry, region, and needs to generate a persona summary and routing rationale. 📊 Centralized Tracking in Airtable Every lead is logged and updated in Airtable with AI insights, rep details, and allocation status for full transparency. 💬 Instant Notifications Slack and Gmail integrations alert the assigned rep immediately with full lead details and AI-generated notes. 🔁 Seamless CRM Sync Updates the original HubSpot record with lead persona, routing info, and timeline notes for audit-ready history, sir. ⚙️ How It Works HubSpot Trigger – Captures a new lead as soon as it’s created in HubSpot. Fetch Contact Data – Retrieves all relevant fields like name, company, and industry. Clean & Format Data – A Code node standardizes and structures the data for consistency. Airtable Record Creation – Logs the lead data into the “Leads” table for centralized tracking. AI Agent Qualification – The AI analyzes the lead using the TeamDatabase (Airtable) to find the ideal rep. Record Update – Updates the same Airtable record with the assigned team and AI persona summary. Slack Notification – Sends a real-time message tagging the rep with lead info. Gmail Notification – Sends a personalized handoff email with context and follow-up actions. HubSpot Sync – Updates the original contact in HubSpot with the assignment details and AI rationale, sir. 🛠️ Setup Steps Trigger Node:** HubSpot → Detect new leads. HubSpot Node:** Retrieve complete lead details. Code Node:** Clean and normalize data. Airtable Node:** Log lead info in the “Leads” table. AI Agent Node:** Process lead and match with sales team. Slack Node:** Notify the designated representative. Gmail Node:** Email the rep with details. HubSpot Node:** Update CRM with AI summary and allocation status, sir. 🔐 Credentials Required HubSpot OAuth2 API** – To fetch and update leads. Airtable Personal Access Token** – To store and update lead data. OpenAI API** – To power the AI qualification and matching logic. Slack OAuth2** – For sending team notifications. Gmail OAuth2** – For automatic email alerts to assigned reps, sir. 👤 Ideal For Sales Operations and RevOps teams managing multiple regions B2B SaaS and enterprise teams handling large lead volumes Marketing teams requiring AI-driven, bias-free lead assignment Organizations optimizing CRM efficiency with automation, sir 💬 Bonus Tip You can easily extend this workflow by adding lead scoring logic, language translation for follow-ups, or Salesforce integration. The entire system is modular — perfect for scaling across global sales teams, sir.

This workflow automates brand monitoring on X by analyzing both the text and the images in posts. It uses multi-modal AI to score brand relevance, filters out noise, logs important mentions in Airtable, and sends real-time alerts to a Telegram group for high-priority posts. What it does Traditional brand monitoring tools often miss the most authentic user content because they only track text. They can't "see" your logo in a photo or your product featured in a video without a direct keyword mention. This workflow acts as an AI agent that overcomes this blind spot. It finds mentions of your brand on X and then uses Google Gemini's multi-modal capabilities to perform a comprehensive analysis of both the text and any attached images. This allows it to understand the full context of a mention, score its relevance to your brand, and take the appropriate action, creating a powerful "visual intelligence" system. How it works The workflow runs on a schedule to find, analyze, and triage brand mentions. Get New Tweets: The workflow begins by using an Apify actor to scrape X for recent posts based on a defined set of search terms (e.g., Tesla OR $TSLA). It then filters these results to find unique mentions not already processed. Check for Duplicates: It cross-references each found tweet with an Airtable base to ensure it hasn't been analyzed before, preventing duplicate work. Analyze Post Content: For each new, unique post, the workflow performs two parallel analyses using Google Gemini: Analyze the Photos: The AI examines the images in the post to describe the scene, identify logos or products, and determine the visual mood. Analyze the Text: A separate AI call analyzes the text of the post to understand its context and sentiment. Final Relevance Check: A "Head Strategist" AI node receives the outputs from both the visual and text analyses. It synthesizes this information to assign a final brand relevance score from 1 to 10. Triage and Action: Based on this score, the workflow automatically triages the post: High Relevance (Score > 7): The post is logged in the Airtable base, and an instant, detailed alert is sent to a Telegram monitoring group. Medium Relevance (Score 4-7): The post is quietly logged in Airtable for later strategic review. Low Relevance (Score < 4): The post is ignored, effectively filtering out noise. Setup Instructions To get this workflow running, you will need to configure your Airtable base and provide credentials for Apify, Google, and Telegram. Required Credentials Apify: You will need an Apify API Token to run the X scraper. Airtable: You will need Airtable API credentials to connect to your base. Google AI: You will need credentials for the Google AI APIs to use the Gemini models. Telegram: You will need a Bot Token and the Chat ID for the channel where you want to receive high-relevance alerts. Of course. Based on the Config node parameters you provided, the setup process is much more centralized. Here is the corrected and rewritten "Step-by-Step Configuration" section. Of course. Here is the rewritten "Step-by-Step Configuration" section with the link to the advanced search documentation. Step-by-Step Configuration Set up Your Airtable Base: Before configuring the workflow, create a new table in your Airtable base. For the workflow to function correctly, this table must contain fields to store the analysis results. Create fields with the following names: postId, postURL, postText, postDateCreated, authorUsername, authorName, sentiment, relevanceScore, relevanceReasoning, mediaPhotosAnalysis, and status. Once the table is created, have your Base ID and Table ID ready to use in the Config node. Edit the Config Node: The majority of the setup is handled in the first Config node. Click on it and edit the following parameters in the "Expressions" tab: searchTerms: Replace the example with the keywords, hashtags, and accounts you want to monitor. The field supports advanced search operators for complex queries. For a full list of available parameters, see the Twitter Advanced Search documentation. airtableBaseId: Paste your Airtable Base ID here. airtableTableId: Paste your Airtable Table ID here. lang: Set the two-letter language code for the posts you want to find (e.g., "en" for English). min_faves: Set the minimum number of "favorites" a post should have to be considered. tweetsToScrape: Define the maximum number of posts the scraper should find in each run. actorId: This is the specific Apify actor for scraping X. You can leave this as is unless you intend to use a different one. Configure the Telegram Node: In the final node, "Send High Relevance Posts to Monitoring Group", you need to manually set the destination for the alerts. Enter the Chat ID for your Telegram group or channel. How to Adapt the Template This workflow is a powerful framework that can be adapted for various monitoring needs. Change the Source:* Replace the Apify* node with a different trigger or data source. You could monitor Reddit, specific RSS feeds, or a news API for mentions. Customize the AI Logic:* The core of this workflow is in the AI prompts. You can edit the prompts in the Google Gemini* nodes to change the analysis criteria. For example, you could instruct the AI to check for specific competitor logos, analyze the sentiment of comments, or identify if the post is from an influential account. Modify the Scoring:** Adjust the logic in the "Switch" node to change the thresholds for what constitutes a high, medium, or low-relevance post to better fit your brand's needs. Change the Actions:* Replace the Telegram* node with a different action. Instead of sending an alert, you could: Create a ticket in a customer support system like Zendesk or Jira. Send a summary email to your marketing team. Add the post to a content curation tool or a social media management platform.

🚀 AI Website Generator & Auto-Deployer Template Transform any idea into a live website in seconds! This AI-powered template generates professional, fully-functional websites from simple text descriptions and automatically deploys them to Netlify. ✨ What You Get Instant Website Creation: Just provide a name and description - our AI agent creates complete HTML files with embedded CSS/JavaScript, ready for immediate deployment. Professional Quality: Every website includes mobile-responsive design, modern CSS Grid/Flexbox layouts, SEO optimization, accessibility features, and smooth animations. No amateur-looking sites - only professional results. Zero-Config Deployment: Automatic Netlify deployment with SSL certificates, CDN distribution, and custom URLs. No technical setup required. 🛠️ AI-Powered Features Smart Content Generation**: Creates contextual, industry-appropriate content (no Lorem Ipsum) Adaptive Design**: Automatically detects website type (portfolio, business, landing page) and adapts accordingly Modern Tech Stack**: HTML5, CSS3 with variables, ES6+ JavaScript, cross-browser compatibility 💼 Perfect For Digital Agencies**: Rapid client prototyping and proposals Freelancers**: Quick turnaround projects Startups**: MVP landing pages Small Businesses**: Professional web presence without coding Marketers**: Campaign landing pages Designers**: Convert concepts to functional prototypes 🔧 Setup Requirements Required API Keys: Netlify Personal Access Token - Enables automatic deployment and domain management Gemini API Key - Powers AI content generation (alternatives: OpenAI GPT, Claude) Airtable Token (Optional) - Project tracking and analytics ⚡ Lightning-Fast Workflow Input project name and description AI generates complete website (under 30 seconds) Automatic quality validation Live deployment to Netlify Optional dashboard tracking 📈 Business Impact 95% time reduction** in development Eliminate coding hours** - focus on strategy Handle multiple projects** simultaneously Consistent quality** across all websites Impress clients** with rapid turnaround 💡 Real Examples "Modern UX designer portfolio" → Clean design with project galleries "Local bakery website with menu" → Appetizing layout with image galleries "SaaS product landing page" → Conversion-focused with pricing tables "Tech conference site" → Event layout with speaker bios and schedules Transform your web development workflow today!

Who is this workflow template for? This workflow template is perfect for freelancers, small business owners, accounting teams, or anyone responsible for managing and recording invoices regularly. If you deal with multiple invoices and spend considerable time manually entering invoice data into a database, this automation will significantly simplify your daily operations and reduce potential errors. What this workflow does The workflow automates the entire invoice logging process. It continuously monitors a designated Google Drive folder every minute for new PDF invoice uploads. Once a new invoice is detected, it is automatically converted from PDF to an image format using the ILovePDF API. After conversion, Google's Gemini AI analyzes the image, intelligently extracting essential details such as vendor name, item description, invoice amount, invoice date, payment date, and bank reference numbers. Finally, this structured data is automatically recorded in an Airtable database (or optionally in a Google Sheet), ensuring organized, accessible records. Detailed Workflow Explanation Step 1: Invoice Detection** Monitors Google Drive for newly uploaded PDF invoices. Step 2: PDF to Image Conversion** Converts PDFs into images using ILovePDF. Step 3: Data Extraction via Gemini AI** Uses Gemini AI to analyze the invoice image. Extracts data such as Vendor, Description, Amount, Invoice Date, Paid Date, and Bank Reference. Provides clear descriptions even when original invoice descriptions are vague or missing by analyzing vendor context. Step 4: Structured Data Storage** Automatically sends extracted data to Airtable or Google Sheets. Step 5: File Management** Moves processed PDF files into a separate "Done" folder to clearly differentiate between processed and unprocessed invoices. Step-by-Step Setup Instructions Set Up Google Drive: Log in to Google Drive and create two folders: One named Invoices (for incoming PDF files) One named Processed (for processed files) Obtain API Credentials: ILovePDF API: Sign up at ILovePDF Developers. Retrieve your API key from your account dashboard. Google Gemini AI API: Register at Google AI and generate an API key. Airtable Database Preparation: Create an Airtable base with the following columns: Vendor (Text) Description (Text) Amount (Number or Text) Invoice Date (Date) Paid Date (Date) Bank Reference (Text) Import and Configure Workflow in n8n: Import the provided workflow JSON file into your n8n instance. Connect your Google Drive, ILovePDF, Google Gemini AI, and Airtable accounts by entering your credentials in their respective nodes. Adjust Workflow Settings: In the Google Drive nodes, ensure your newly created Invoices and Processed folders are correctly selected. Update the ILovePDF public key in the appropriate HTTP Request node. Customize the Gemini AI prompt to refine or expand data extraction according to your specific needs. Testing Your Setup: Upload a sample PDF invoice into the Invoices folder. Execute the workflow by clicking Test Workflow in n8n and verify if data extraction and Airtable logging operate correctly. Airtable Column Specifications Ensure your Airtable includes the following structure: Vendor**: Single Line Text Description**: Single Line Text Amount**: Currency or Single Line Text Invoice Date**: Date (formatted as YYYY-MM-DD) Paid Date**: Date (formatted as YYYY-MM-DD) Bank Reference**: Single Line Text How to Customize the Workflow System Prompt:** Adjust the AI instructions by modifying the prompt text to focus on additional or fewer invoice details. Structured Output Parser:** Modify the JSON schema in the parser node to match the structure and data points your project specifically requires: By following these instructions, you’ll have a fully automated, reliable system for handling and logging invoice data, significantly enhancing your productivity.

How it Works: Trigger: The workflow is triggered by a webhook, initiated by an Airtable automation. This automation sends the Book or Chapter record ID and the desired action (e.g., "Generate Book Details," "Generate Chapters," "Generate Chapter Research," "Generate Chapter Content"). Action Routing: A "Switch" node directs the workflow based on the action query parameter received from the webhook. This determines which part of the book creation process will be executed. Data Retrieval: The workflow fetches the relevant book or chapter data from Airtable using the provided recordId. AI Processing: Book Details Generation: If the action is "Generate Book Details," an AI Agent (powered by a Large Language Model (LLM) like Google Gemini and the Perplexity search tool) researches the book idea. It focuses on crafting a compelling book description, identifying the target audience, and conducting general book research to maximize bestseller potential. The research brief is then saved back to Airtable. Chapter Generation: If the action is "Generate Chapters," an LLM generates 7-10 chapter titles and descriptions based on the book idea and previous research. A structured output parser ensures the chapter data is in the correct format. The chapters are then split into individual items and saved as separate records in the "Chapter" table in Airtable, linked to the main book record. Chapter Research Generation: If the action is "Generate Chapter Research," another AI Agent conducts in-depth research on a specific chapter, using the Perplexity search tool multiple times. It focuses on finding stories, case studies, historical events, and expert perspectives to make the chapter engaging and credible. The research is saved back to the "Chapter" record in Airtable. Chapter Content Generation: If the action is "Generate Chapter Content," an LLM writes the full content of the chapter, using the research gathered in the previous step, the overall book research, and the chapter description. The generated content is saved back to the "Chapter" record in Airtable. Airtable Updates: In each of the AI processing steps, the workflow updates the corresponding Airtable record (either "Book" or "Chapter") with the generated results (research, chapter details, or content) and sets the "Action" field back to "Idle." Set Up Steps: Airtable Setup (Estimated time: 10-15 minutes): Copy the Airtable base blueprint: https://airtable.com/appfkz4KUlKvOjtbp/shra78TlDfqLRdSfT. This will create the "Book" and "Chapter" tables with the necessary fields. In the "Book" table, create three Airtable Automations: Trigger: When a record matches conditions -> Action is Generate Book Details Action: Run a script. Use the following script: let autoRoute = input.config(); await fetch(autoRoute.webhookUrl + "?recordId=" + autoRoute.recordId + "&action=" + autoRoute.action); In the script action's configuration, add three "Input variables": webhookUrl (map it to your n8n webhook URL, obtained in the next step) recordId (map it to the Airtable record ID) action (map it to Action) Repeat this process to create two more automations in the "Book" table, identical except triggered when Action is Generate Chapters, respectively. In the "Chapter" table, create two Airtable Automations: Trigger: When a record matches conditions -> Action is Generate Chapter Research Action: Run a script (use the same script as above, with the same input variables). Create a second automation, identical except triggered when Action is Generate Chapter Content. n8n Setup (Estimated time: 15-20 minutes): Import the provided JSON workflow into n8n. Webhook Node: Copy the "Test URL" from the Webhook node. This is the webhookUrl you'll use in the Airtable automations. Important: Once you've tested and are ready to go live, switch to the "Production URL." Airtable Nodes: Configure all Airtable nodes (there are eight). You'll need to connect your Airtable account using OAuth 2. Select the correct Base ("Book Agency \[v1] Cobuild" or whatever you named it) and Table ("Book" or "Chapter") for each node. The field mappings are already defined in the template, but double-check them. LLM Nodes (Google Gemini & OpenAI): Connect your Google Gemini and OpenAI accounts to the respective LLM nodes. You'll need API keys for both. You may also configure different LLM Models. Perplexity Nodes Connect your Perplexity AI API to the Perplexity nodes. You'll need API keys for that. Activate the workflow. Testing (Estimated Time: 5-10 minutes): Go to your Airtable "Book" table. Create a New Record. Fill in the "Idea" field with a book concept. Change the "Action" field to "Generate Book Details". The Airtable automation should trigger, sending a request to your n8n webhook. Monitor the n8n execution log to see the workflow in action. Check the Airtable record to see if the "Research" field is populated. Repeat the testing for Generate Chapters, Generate Chapter Research and Generate Chapter Content.

How It Works Trigger Watches for new emails with attachments in a Gmail label. Extract Data Extracts job code from the email subject (e.g., FN-001) Extracts raw text from the attached CV (PDF) AI Parsing Uses Google Gemini to parse the CV and extract: Name Email Years of experience Skills Job Lookup Uses the extracted job code to retrieve job details from Airtable. AI Scoring Compares applicant data with job requirements Scores from 1–100 Generates a brief reasoning summary (in Bahasa Indonesia) Log to Airtable Saves applicant data, score, and AI notes to the "Applications" table. Setup Instructions Prepare Airtable Base Job Posts Table Columns: Job Code, Job Title, Required Skills, Minimum Experience, Job Description Applications Table Columns: Applicant Name, Email, Score, Notes Include a linked field to the Job Posts table Add Credentials in n8n Gmail Google AI (Gemini) Airtable Configure Nodes Trigger: Set Gmail filter (e.g., label:job-applications) Extract Job Code: Verify regex format, default is ([A-Z]{2}-\d{3}) Airtable Nodes: Select your base and table in: "Find Job Post..." "Save Applicant..." Activate Workflow Save and enable the workflow New applications will be processed automatically