by getBible
Overview The Get Bible Query Workflow is a modular and self-standing workflow designed to retrieve scriptures dynamically based on structured input. It serves as an intermediary layer that extracts references, queries the GetBible API, and returns scriptures in a standardized JSON format. This workflow is fully prepared for integration—simply call it from another workflow with the required JSON input, and it will return the requested scripture data. Who Is This For? This workflow is ideal for developers, Bible study apps, research tools, and dynamic scripture-based projects that need seamless access to scriptural content without direct API interaction. ✅ Use Cases: Bible Study Apps** → Embed scripture retrieval functionality. Research & Theology Tools** → Fetch structured verse data. Dynamic Content Generation** → Integrate real-time scripture references. Sermon Preparation** → Automate scripture lookups. How It Works Trigger Workflow → This workflow is designed to be called from another workflow with a structured JSON input. Receive Input → Accepts a JSON object containing references, translation, and API version. Extract References → Parses single verses, comma-separated lists, and ranged passages. Query API → Sends structured requests to the GetBible API. Format Response → Returns structured JSON output, maintaining API response consistency. JSON Input Structure References** → Should include the book name, chapter, and verse(s). Multiple Verses** → Separated by commas (e.g., John 3:16,18). Verse Ranges** → Defined with a dash (e.g., John 3:16-18). Translation** → Choose from the supported translations. API Version** → Currently supports v2. Example JSON Input { "references": [ "1 John 3:16", "Jn 3:16", "James 3:16", "Rom 3:16" ], "translation": "kjv", "version": "v2" } Example API Response { "result": { "kjv_62_3": { "translation": "King James Version", "abbreviation": "kjv", "book_name": "1 John", "chapter": 3, "ref": ["1 John 3:16"], "verses": [ { "chapter": 3, "verse": 16, "name": "1 John 3:16", "text": "Hereby perceive we the love of God, because he laid down his life for us: and we ought to lay down our lives for the brethren." } ] } } } 💡 Fully structured and formatted response – ready for seamless integration. Integration and Usage The GetBible Query Workflow is designed for immediate use. Simply call it from another workflow and pass the appropriate JSON object as input, and it will return the requested scripture passages. ✔️ No additional configuration is required. ✔️ Designed for fast, reliable, and structured scripture retrieval. ✔️ Fully compatible with GetBible API responses. Why Use This Workflow? ✔️ Fast & Reliable → Direct API integration for efficient queries. ✔️ Flexible Queries → Supports single, multi-verse, and ranged requests. ✔️ Agent-Compatible → Easily integrates into automated workflows. ✔️ No Code Needed → Just configure the JSON input and run the workflow. Next Steps 🔗 API Support 📖 API Documentation 💬 Need help? Join the community for support! 🚀
by Preston Zeller
How It Works This workflow automates the real estate lead qualification process by leveraging property data from BatchData. The automation follows these steps: When a new lead is received through your CRM webhook, the workflow captures their address information It then makes an API call to BatchData to retrieve comprehensive property details A sophisticated scoring algorithm evaluates the lead based on property characteristics like: Property value (higher values earn more points) Square footage (larger properties score higher) Property age (newer constructions score higher) Investment status (non-owner occupied properties earn bonus points) Lot size (larger lots receive additional score) Leads are automatically classified into categories (high-value, qualified, potential, or unqualified) The workflow updates your CRM with enriched property data and qualification scores High-value leads trigger immediate follow-up tasks for your team Notifications are sent to your preferred channel (Slack in this example) The entire process happens within seconds of receiving a new lead, ensuring your sales team can prioritize the most valuable opportunities immediately.. Who It's For This workflow is perfect for: Real estate agents and brokers looking to prioritize high-value property leads Mortgage lenders who need to qualify borrowers based on property assets Home service providers (renovators, contractors, solar installers) targeting specific property types Property investors seeking specific investment opportunities Real estate marketers who want to segment audiences by property value Home insurance agents qualifying leads based on property characteristics Any business that bases lead qualification on property details will benefit from this automated qualification system. About BatchData BatchData is a comprehensive property data provider that offers detailed information about residential and commercial properties across the United States. Their API provides: Property valuation and estimates Ownership information Property characteristics (size, age, bedrooms, bathrooms) Tax assessment data Transaction history Occupancy status (owner-occupied vs. investment) Lot details and dimensions By integrating BatchData with your lead management process, you can automatically verify and enrich leads with accurate property information, enabling more intelligent lead scoring and routing based on actual property characteristics rather than just contact information. This workflow demonstrates how to leverage BatchData's property API to transform your lead qualification process from manual research into an automated, data-driven system that ensures high-value leads receive immediate attention.
by Jonathan
This workflow automatically posts a message in Slack when a new invoice is uploaded in Stripe, and it updates the fields in the HubSpot CRM. Prerequisites A Slack account and credentials A HubSpot account and credentials A Stripe account and credentials Nodes Stripe Trigger node triggers the workflow when a new invoice is uploaded. IF nodes filter the invoices that don't have a PO number and if there is no deal for the PO. HubSpot nodes retrieve deals with the specific PO number and update the deal status to 'paid'. Slack nodes post messages about the deals in a Slack channel.
by Automate With Marc
📊 Dynamic Portfolio Advisor – Daily Stock Market Intelligence with Google Sheets Description: This advanced AI-powered n8n workflow automatically delivers a daily market intelligence briefing tailored to your stock holdings portfolio stored in Google Sheets. It uses real-time data from Perplexity AI, combines it with your portfolio, and generates personalized insights, risk alerts, and trade suggestions — all delivered via Telegram or any messaging app of your choice. For step-by-step build of workflows like this, check out: https://www.youtube.com/@Automatewithmarc ⚙️ How It Works: 🕒 Daily Trigger Starts every day at a scheduled time (default: 10 AM) to fetch the most recent market data. 📈 Holdings Fetch Reads your current portfolio dynamically from Google Sheets — no hardcoding required. 🧠 AI Analysis Agent Combines: Market headlines Company-specific developments Macroeconomic updates And analyzes how they might affect your holdings. 🔍 Perplexity Web Research Tool Finds and summarizes the most relevant stock market news from the past 24 hours. 💬 Telegram Delivery Sends a customized summary of: Market highlights Asset-specific impacts Opportunities and risks Actionable trade ideas (buy/sell/hold) 🛠️ Tools & Integrations: Google Sheets (live holdings feed) Perplexity AI (real-time market research) OpenAI GPT (financial summarization) Telegram (output, customizable) 💡 Use Cases: Portfolio-aware market intelligence Automated investor briefing assistant Risk alert + opportunity scanner Daily trade idea generator Finance bloggers or equity analysts streamlining prep work 📍Note: You can easily replace Telegram with Slack, Email, Notion, or any output tool supported by n8n. This template is perfect for active investors, financial advisors, or automation-savvy traders who want to turn AI and data into actionable daily signals.
by Maximiliano Rojas-Delgado
Turn Your Ideas into Videos—Right from Google Sheets! This workflow helps you make cool 8-second videos using Fal.AI and Veo 3, just by typing your idea into a Google Sheet. You can even choose if you want your video to have sound or not. It’s super easy—no tech skills needed! Why use this? Just type your idea in a sheet—no fancy tools or uploads. Get a video link back in the same sheet. Works with or without sound—your choice! How does it work? You write your idea, pick the video shape, and say if you want sound (true or false) in the Google Sheet. n8n reads your idea and asks Fal.AI to make your video. When your video is ready, the link shows up in your sheet. What do you need? A Google account and Google Sheets connected with service account (check this link for reference) A copy of the following Google Spreadsheet: Spreadsheet to copy An OpenAI API key A Fal.AI account with some money in it That’s it! Just add your ideas and let the workflow make the videos for you. Have fun creating! if you have any questions, just contact me at max@nervoai.com
by n8n Team
The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
by Amjid Ali
Detailed Title "Triathlon Coach AI Workflow: Strava Data Analysis and Personalized Training Insights using n8n" Description This n8n workflow enables you to build an AI-driven virtual triathlon coach that seamlessly integrates with Strava to analyze activity data and provide athletes with actionable training insights. The workflow processes data from activities like swimming, cycling, and running, delivers personalized feedback, and sends motivational and performance improvement advice via email or WhatsApp. Workflow Details Trigger: Strava Activity Updates Node:** Strava Trigger Purpose:** Captures updates from Strava whenever an activity is recorded or modified. The data includes metrics like distance, pace, elevation, heart rate, and more. Integration:** Uses Strava API for real-time synchronization. Step 1: Data Preprocessing Node:** Code Purpose:** Combines and flattens the raw Strava activity data into a structured format for easier processing in subsequent nodes. Logic:** A recursive function flattens JSON input to create a clean and readable structure. Step 2: AI Analysis with Google Gemini Node:** Google Gemini Chat Model Purpose:** Leverages Google Gemini's advanced language model to analyze the activity data. Functionality:** Identifies key performance metrics. Provides feedback and insights specific to the type of activity (e.g., running, swimming, or cycling). Offers tailored recommendations and motivational advice. Step 3: Generate Structured Output Node:** Structure Output Purpose:** Processes the AI-generated response to create a structured format, such as headings, paragraphs, and bullet lists. Output:** Formats the response for clear communication. Step 4: Convert to HTML Node:** Convert to HTML Purpose:** Converts the structured output into an HTML format suitable for email or other presentation methods. Output:** Ensures the response is visually appealing and easy to understand. Step 5: Send Email with Training Insights Node:** Send Email Purpose:** Sends a detailed email to the athlete with performance insights, training recommendations, and motivational messages. Integration:** Utilizes Gmail or SMTP for secure and efficient email delivery. Optional Step: WhatsApp Notifications Node:** WhatsApp Business Cloud Purpose:** Sends a summary of the activity analysis and key recommendations via WhatsApp for instant access. Integration:** Connects to WhatsApp Business Cloud for automated messaging. Additional Notes Customization: You can modify the AI prompt to adapt the recommendations to the athlete's specific goals or fitness levels. The workflow is flexible and can accommodate additional nodes for more advanced analysis or output formats. Scalability: Ideal for individual athletes or coaches managing multiple athletes. Can be expanded to include additional metrics or insights based on user preferences. Performance Metrics Handled: Swimming: SWOLF, stroke count, pace. Cycling: Cadence, power zones, elevation. Running: Pacing, stride length, heart rate zones. Implementation Steps Set Up Strava API Key: Log in to Strava Developers to generate your API key. Integrate the API key into the Strava Trigger node. Configure Google Gemini Integration: Use your Google Gemini (PaLM) API credentials in the Google Gemini Chat Model node. Customize Email and WhatsApp Messaging: Update the Send Email and WhatsApp Business Cloud nodes with the recipient’s details. Automate Execution: Deploy the workflow and use n8n's scheduling features or cron jobs for periodic execution. GET n8n Now N8N COURSE n8n Book Developer Notes Author:** Amjid Ali improvements. Resources:** See in Action: Syncbricks Youtube PayPal: Support the Developer Courses : SyncBricks LMS By using this workflow, triathletes and coaches can elevate training to the next level with AI-powered insights and actionable recommendations.
by Matt F.
AI Customer-Support Assistant that auto-maps any business site, answers WhatsApp in real time, and lets you earn or save thousands by replacing pricey SaaS chat tools. ⚡ What the workflow does Live “AI employee”* - the bot crawls pages on demand (products, policies, FAQs) so you *never** upload documents or fine-tune a model. No-code setup** - Drop in API keys, paste your domain, publish the webhook—ready in \~15 min. Chat memory** - each conversation turn is written to Supabase/Postgres and automatically replayed into the next prompt, letting the assistant remember context so follow-up questions feel natural and coherent even across long sessions. WhatsApp ready** - Free-form replies inside the 24-hour service window, automatically switches to a template when required (recommended by Meta). 🚀 Why you’ll love it | Benefit | Impact | | ------------------------- | --------------------------------------------------------------------- | | Zero content training | Point the AI Agent at any domain → go live. | | Save or earn money | Replace pricey SaaS chat tools or sell white-label bots to clients. | | Channel-agnostic | Ships with WhatsApp; swap one node for Telegram, Slack, or web chat. | | Flexible voice | Adjust tone & language by editing one prompt line. | 🧰 Prerequisites (all free-tier friendly) OpenAI key Meta WhatsApp Cloud API number + permanent token (easy setup) Supabase (or Postgres) URL for chat memory (easy setup) 🛠 5-step setup Import the template into n8n. Add credentials for OpenAI, WhatsApp, and Supabase. Enter your root domain in the root\_url variable. Point Meta’s Webhook to the n8n URL. Hit Execute Trigger and send “Hi” from WhatsApp—watch the bot answer with live data. 🔄 Easy to extend Voice & language** – change wording in the System Prompt. Escalation** – add an “If fallback” branch → Zendesk, email, live agents. Extra channels** – duplicate the reply node for Telegram or Slack. Commerce API hooks** – plug in Shopify, Woo, Stripe for order status or payments. 💡 Monetization ideas Replace costly SaaS seats.* Deploy the bot on your own server and *stop paying \$300–\$500 every month for third-party “AI support” platforms. Sell it as a service.* Spin up a branded instance for local shops, clinics, or e-commerce stores and *charge each client \$300–\$500 per month**—setup time is under 15 minutes. Upsell premium coverage (24/7 human hand-off) once the bot handles routine questions. Embed product links in answers and earn affiliate or upsell revenue automatically. Spin it up, connect a domain and a phone number, and you—or your customers—get enterprise-grade support without code, training, or ongoing licence fees.
by PretenderX
This template automates sending a DingTalk message on new Azure Dev Ops Pull Request Created Events. It uses a MySQL database to store mappings between Azure users and DingTalk users; so the right users get notified. Set up instructions Define the path value of ReceiveTfsPullRequestCreatedMessage Webhook node of your own, copy the webhook url to create a Azure DevOps ServiceHook that call webhook with Pull Request Created event. In order to configure the LoadDingTalkAccountMap node, you need to create a MySQL table as below: |Name|Type|Length|Key| |-|-|-|-| |TfsAccount|varchar|255| |UserName|varchar|255| |DingTalkMobile|varchar|255| You can customize the Ding Talk message content by editing the BuildDingTalkWebHookData node. Define the URL of SendDingTalkMessageViaWebHook Http Request node as your Ding Talk group chat robot webhook URL. Send test of production message from Azure DevOps to test.
by Yaron Been
Description This workflow automatically generates Facebook ad headlines for your product using OpenAI and evaluates their quality using custom AI-generated criteria. It ensures you get high‑quality, scroll‑stopping headlines without needing a copywriter. Overview This workflow captures a product description via a form, generates a Facebook ad headline, invents a scoring rubric, evaluates the headline against it, and optionally loops for revisions — all autonomously. Ideal for marketers and media buyers looking to scale creative testing. Tools Used n8n**: The automation platform that powers and orchestrates the entire workflow. OpenAI**: Used for headline generation, scoring criteria creation, and evaluation logic. (Optional)** Google Sheets / Notion / Email: For logging approved headlines or sharing results. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Connect OpenAI: Add your OpenAI credentials to the GPT nodes. Customize the Prompt (optional): Tweak the system prompt inside the Set_PromptForHeadline node. Add Output Handling (optional): Connect the “NO” path in the If_NeedMoreIterations node to Google Sheets, Slack, etc. (Optional) Add loop limits or storage logic to manage iterations or save results. Use Cases Media Buyers**: Generate and test hooks at scale with no creative bottlenecks. Solo Marketers**: Get high-converting headlines even without a copywriter. Agencies**: Streamline copy testing and evaluation in client campaigns. Startup Teams**: Automate creative generation during product launches or A/B tests. Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Hashtags #n8n #openai #automation #copywriting #facebookads #headlines #aicopy #promptengineering #marketingautomation #nocode #llm #creativeautomation #mediabuying #adtesting #adcreative #marketingtools #digitalmarketing #copytesting #scalablecreative #chatgpt #adhooks #growthmarketing #automatedworkflows #aiworkflow #creativeops #marketingops #growthtools
by Thibaud
Title: Automatic Strava Titles & Descriptions Generation with AI Description: This n8n workflow connects your Strava account to an AI to automatically generate personalized titles and descriptions for every new cycling activity. It leverages the native Strava trigger to detect new activities, extracts and formats ride data, then queries an AI agent (OpenRouter, ChatGPT, etc.) with an optimized prompt to get a catchy title and inspiring description. The workflow then updates the Strava activity in real time, with zero manual intervention. Key Features: Secure connection to the Strava API (OAuth2) Automatic triggering for every new activity Intelligent data preparation and formatting AI-powered generation of personalized content (title + description) Instant update of the activity on Strava Use Cases: Cyclists wanting to automatically enhance their Strava rides Sports content creators Community management automation for sports groups Prerequisites: Strava account Strava OAuth2 credentials set up in n8n Access to a compatible AI agent (OpenRouter, ChatGPT, etc.) Benefits: Saves time Advanced personalization Boosts the appeal of every ride to your community
by dataplusminus+-
🎯 Project Purpose This project automates the process of collecting and managing new leads submitted through a web form. It eliminates the need for manual data entry and ensures that each lead is: Properly recorded and time-stamped in a structured format Automatically communicated to the sales or support team Ready for follow-up, with a reminder system in place It’s a lightweight but effective solution suitable for freelancers, small teams, and growing businesses that want to streamline their lead intake process. 🛠️ Tools & Technologies Used Google Forms / Web Form** – Frontend for capturing leads Google Sheets** – Central database for storing lead information n8n** – Automation platform that connects and coordinates all services Gmail** – Handles email notifications for new leads Slack* *(optional) – Provides instant team notifications Date & Time nodes** – Tracks and manages lead response timing Conditional (IF) nodes** – Filters out duplicate and incomplete entries 🔄 Workflow Overview ✨ Key Features ✅ No-code integration using n8n ✅ Instant alerts via Gmail and/or Slack ✅ Google Sheets as an easily accessible backend ✅ Modular design — easy to expand with CRM tools (like HubSpot) ✅ Clean JSON structure and logic, beginner-friendly 📈 Possible Improvements Add email validation via external API (e.g., NeverBounce, Hunter) Integrate with a CRM for deeper automation Add lead scoring based on answers Include automatic follow-up emails after X days Schedule weekly summary reports via email 🧑🏻💻 Creator Information Developed by: Adem Tasin Adem T. 🌐 Website: Dataplusminus+- 📧 Email:dataplusminuss@gmail.com 💼 LinkedIn: Adem Tasin