by Agentick AI
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. **This n8n template automates candidate outreach, call transcription, and structured feedback capture for HR teams and recruiters. It triggers on a new candidate row added in a Google Sheet, initiates a call using Vapi.ai, processes the transcript using Google Gemini, extracts key information like CTC, experience, and notice period, and then updates the same Google Sheet with parsed insights. This is ideal for recruiters or HR teams conducting high-volume candidate outreach and wanting to scale initial data collection using automated voice bots and AI transcription analysis.** How it works Trigger: Listens for new rows added to a Google Sheet (e.g., a new candidate lead). Call Initiation: Uses Vapi.ai to make a phone call to the candidate using an assistant bot. Transcript Retrieval: After the call, fetches the conversation transcript from the Vapi API. AI Transcript Analysis: Google Gemini parses the transcript and extracts structured fields like: Work experience Current & expected CTC Notice period & negotiability Work preferences and location Data Mapping: Extracted insights are mapped to structured JSON fields. Google Sheet Update: The same row in the source Sheet is updated with the collected information. Use Cases Pre-screening calls for job applicants Collecting missing candidate information asynchronously Replacing manual HR data entry with AI-powered automation Smart CRM updates from voice interactions Requirements Before you run this workflow, ensure the following: ✅ Google account with access to Google Sheets API ✅ Vapi.ai account with: Assistant ID Phone number ID Active API key ✅ Google Gemini API (via PaLM) enabled ✅ n8n version 1.40.0 or later with relevant credentials configured How to use Import the workflow into n8n. Set up your credentials for: Google Sheets Trigger Google Sheets Vapi.ai (add Bearer token) Google Gemini Replace the placeholder values in: Assistant ID Phone number ID Google Sheet ID and tab Start the workflow and add a row to the Google Sheet. Wait for the automated call and let the AI extract and populate the data. Customising this workflow Replace Google Gemini with OpenAI or Claude if preferred. Add sentiment analysis on the transcript using an LLM. Modify the Sheet column structure to add additional fields. Add a filter node to skip candidates with incomplete phone numbers. Use a Webhook trigger instead of Google Sheets to integrate with job portals or ATS.
by Yang
Who is this for? This template is for sales teams, agencies, or local service providers who want to quickly generate cold outreach lists and automatically call local businesses with a Vapi AI assistant. It’s perfect for automating cold calls from scraped local listings with no manual dialing or research. What problem is this workflow solving? Finding leads and initiating outreach calls can be time-consuming. This workflow automates the process: it scrapes business listings from Google Maps using Dumpling AI, extracts phone numbers, filters out incomplete data, formats the numbers, and uses Vapi to make outbound AI-powered calls. Every call is logged in Google Sheets for follow-up and tracking. What this workflow does Starts manually and pulls search queries (e.g., "plumbers in Austin") from Google Sheets. Sends each query to Dumpling AI’s Google Maps scraping endpoint. Splits the returned business data into individual leads. Extracts key info like business name, website, and phone number. Filters to only keep leads with valid phone numbers. Formats phone numbers for Vapi dialing (adds +1). Calls each business using Vapi AI. Logs each successful call in a Google Sheet. Setup Google Sheets Setup Create a sheet with business search queries in the first column (e.g., best+restaurants+in+Chicago) Make sure the tab name is set and authorized in your credentials. Connect your Google Sheets account in the Get Search Keywords from Google Sheets node. Dumpling AI Setup Go to dumplingai.com Generate an API Key and connect it as a header token in the Scrape Google Map Businesses using Dumpling AI node Vapi Setup Sign into Vapi and create an assistant Get your assistantId and phoneNumberId Insert these into the JSON payload of the Initiate Vapi AI Call to Business node Add your Vapi API key to the credentials section Call Logging Create another tab in your sheet (e.g., “leads”) with these headers: company name phone number website This will be used in the Log Called Business Info to Sheet node How to customize this workflow to your needs Modify the business search terms in your Google Sheet to target specific industries or locations. Add filters to exclude certain businesses based on ratings, keywords, or location. Update your Vapi assistant script to match the type of outreach or pitch you’re using. Add additional integrations (e.g., CRM logging, Slack notifications, follow-up emails). Change the trigger to run on a schedule or webhook instead of manually. Nodes and Functions Breakdown Start Workflow Manually: Initiates the automation manually for testing or controlled runs. Get Search Keywords from Google Sheets: Reads search phrases from the spreadsheet. Scrape Google Map Businesses using Dumpling AI: Sends each search query to Dumpling AI and receives matching local business data. Split Each Business Result: Breaks the returned array of businesses into individual records for processing. Extract Business Name, Phone and website: Extracts title, phone, and website from each business record. Filter Valid Phone Numbers Only: Ensures only entries with a phone number move forward. Format Phone Number for Calling: Adds a +1 country code and strips non-numeric characters. Initiate Vapi AI Call to Business: Uses the business name and number to initiate a Vapi AI outbound call. Log Called Business Info to Sheet: Appends business details into a Google Sheet for tracking. Notes You must have valid API keys and authorized connections for Dumpling AI, Google Sheets, and Vapi. Make sure to handle API rate limits if you're running the workflow on large datasets. This workflow is optimized for US-based leads (+1 country code); adjust the formatting node if calling internationally.
by Don Jayamaha Jr
⏱️ Analyze Tesla (TSLA) short-term market structure and momentum using 6 technical indicators on the 15-minute timeframe. This AI agent tool is part of the Tesla Quant Trading AI Agent system. It is designed to detect intraday shifts in volatility, trend strength, and potential reversal signals. ⚠️ Not standalone. This agent is triggered via Execute Workflow by the Tesla Financial Market Data Analyst Tool. 🔌 Requires: Tesla Quant Technical Indicators Webhooks Tool Alpha Vantage Premium API Key 📊 What It Does This workflow pulls the latest 20 data points for 6 key technical indicators from a webhook-powered source, then uses GPT-4.1 to interpret market momentum and structure: Connected Indicators: RSI (Relative Strength Index)** MACD (Moving Average Convergence Divergence)** BBANDS (Bollinger Bands)** SMA (Simple Moving Average)** EMA (Exponential Moving Average)** ADX (Average Directional Index)** The output is a structured JSON with: Market summary Timeframe (15m) Indicator values 📋 Sample Output { "summary": "TSLA shows fading momentum. RSI dropped below 60, MACD is flattening, and BBANDS are tightening. Expect short-term consolidation.", "timeframe": "15m", "indicators": { "RSI": 58.3, "MACD": { "macd": -0.020, "signal": -0.018, "histogram": -0.002 }, "BBANDS": { "upper": 183.10, "lower": 176.70, "middle": 179.90, "close": 177.60 }, "SMA": 178.20, "EMA": 177.70, "ADX": 19.6 } } 🧠 Agent Components | Module | Role | | --------------------- | -------------------------------------------------------- | | Webhook Data Node | Calls /15minData endpoint for Alpha Vantage indicators | | LangChain Agent | Parses indicator payloads and generates reasoning | | OpenAI GPT-4.1 | Powers the AI logic to interpret technical structure | | Memory Module | Maintains session consistency for multi-agent calls | 🛠️ Setup Instructions Import Workflow into n8n Name it: Tesla_15min_Indicators_Tool Configure Webhook Source Install and publish: Tesla_Quant_Technical_Indicators_Webhooks_Tool Ensure /15minData is publicly reachable (or tunnel-enabled) Add Credentials Alpha Vantage API Key (HTTP Query Auth) OpenAI GPT-4.1 (OpenAI Chat Model) Link as Sub-Agent This workflow is not triggered manually. It is executed using Execute Workflow by: 👉 Tesla_Financial_Market_Data_Analyst_Tool Pass in: message (optional) sessionId (for short-term memory linkage) 📌 Sticky Notes Summary 🟢 Trigger Integration – Receives sessionId and message from parent 🟡 Webhook Fetcher – Pulls Alpha Vantage data from /15minData 🧠 GPT-4.1 Reasoning – Produces structured JSON insight 🔵 Session Memory – Maintains evaluation flow across tools 📘 Tool Description – Explains indicator use and AI output format 🔒 Licensing & Author © 2025 Treasurium Capital Limited Company All logic, formatting, and agent design are protected under copyright. No resale or public re-use without permission. Created by: Don Jayamaha Creator Profile: https://n8n.io/creators/don-the-gem-dealer/ 🚀 Build faster intraday Tesla trading models using clean 15-minute indicator insights—processed by AI. Required by the Tesla Financial Market Data Analyst Tool.
by Ron
Objective In industry and production sometimes machine data is available in databases. That might be sensor data like temperature or pressure or just binary information. In this sample flow reads machine data and sends an alert to your SIGNL4 team when the machine is down. When the machine is up again the alert in SIGNL4 will get closed automatically. Setup We simulate the machine data using a Notion table. When we un-check the Up box we simulate a machine-down event. In certain intervals n8n checks the database for down items. If such an item has been found an alert is send using SIGNL4 and the item in Notion is updates (in order not to read it again). Status updates from SIGNL4 (acknowledgement, close, annotation, escalation, etc.) are received via webhook and we update the Notion item accordingly. This is how the alert looks like in the SIGNL4 app. The flow can be easily adapted to other database monitoring scenarios.
by Don Jayamaha Jr
📅 Analyze Tesla’s daily trading structure with AI using 6 Alpha Vantage indicators. This tool evaluates long-term trend health, volatility patterns, and potential reversal signals at the 1-day timeframe. Designed for use within the Tesla Financial Market Data Analyst Tool, this agent helps swing and position traders anchor macro sentiment. ⚠️ Not standalone. Must be executed via Execute Workflow 🔌 Requires: Tesla Quant Technical Indicators Webhooks Tool Alpha Vantage Premium API Key OpenAI GPT-4.1 credentials 🔍 What It Does This tool queries a secured webhook (/1dayData) to retrieve real-time, trimmed JSON data for: RSI (Relative Strength Index)** BBANDS (Bollinger Bands)** SMA (Simple Moving Average)** EMA (Exponential Moving Average)** ADX (Average Directional Index)** MACD (Moving Average Convergence Divergence)** These values are then passed to a LangChain AI Agent powered by GPT-4.1, which returns: A 2–3 sentence market condition summary Structured indicator values Timeframe tag ("1d") 📋 Sample Output { "summary": "TSLA shows consolidation on the daily chart. RSI is neutral, BBANDS are contracting, and MACD is flattening.", "timeframe": "1d", "indicators": { "RSI": 51.3, "BBANDS": { "upper": 192.80, "lower": 168.20, "middle": 180.50, "close": 179.90 }, "SMA": 181.10, "EMA": 179.75, "ADX": 15.8, "MACD": { "macd": -0.25, "signal": -0.20, "histogram": -0.05 } } } 🧠 Agent Components | Component | Description | | ----------------------------- | -------------------------------------------------- | | 1day Data (HTTP Node) | Pulls latest data from secured /1dayData webhook | | OpenAI Chat Model | GPT-4.1 powers the analysis logic | | Tesla 1day Indicators Agent | LangChain agent performing interpretation | | Simple Memory | Short-term session continuity | 🛠️ Setup Instructions Import Workflow into n8n Name: Tesla_1day_Indicators_Tool Add Required Credentials Alpha Vantage Premium (via HTTP Query Auth) OpenAI GPT-4.1 (Chat Model) Install Webhook Fetcher Required: Tesla Quant Technical Indicators Webhooks Tool Endpoint /1dayData must be active Execution Context This tool is only triggered via: 👉 Tesla Financial Market Data Analyst Tool Inputs expected: message: optional context sessionId: session memory linkage 📌 Sticky Notes Overview 📘 Tesla 1-Day Indicators Tool – Purpose and integration 📡 Webhook Fetcher – Pulls daily Alpha Vantage data via HTTPS 🧠 GPT-4.1 Model – Reasoning for trend classification 🔗 Sub-Agent Trigger – Used only by Financial Market Analyst 🧠 Memory Buffer – Ensures consistent session logic 🔒 Licensing & Support © 2025 Treasurium Capital Limited Company This workflow—including prompts, logic, and formatting—is protected IP. 🔗 Don Jayamaha – LinkedIn 🔗 Creator Profile 🚀 Evaluate long-term Tesla price behavior with AI-enhanced technical analysis—critical for swing trading strategy. Required by the Tesla Financial Market Data Analyst Tool.
by KlickTipp
Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works Gravity Forms Customer Feedback Form Integration: This workflow streamlines the process of handling customer feedback submitted via Gravity Forms. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers and converting dates. Key Features Gravity Forms Trigger Captures new form submissions from Gravity Forms via a webhook and initiates the workflow. Data Processing and Transformation Formats and validates essential data: Converts phone numbers to numeric-only format with international prefixes. Transforms dates (e.g., birthdays) to UNIX timestamps. Calculates and scales numeric responses (e.g., webinar ratings). Parses webinar selections into timestamps for structured scheduling. Subscriber Management in KlickTipp Adds or updates contacts in a KlickTipp subscriber list. Includes custom field mappings such as: Personal details (name, email, birthday, phone number). Feedback and preferences (e.g., webinar ratings, chosen sessions). Structured answers from form responses. Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling Ensures invalid or empty data is handled gracefully, preventing workflow interruptions. Setup Instructions Install and Configure Nodes: Set up the Webhook, Set, and KlickTipp nodes in your n8n instance. Authenticate your Gravity Forms and KlickTipp accounts. Prepare Custom Fields in KlickTipp: Create fields in KlickTipp to align with the form submission data, such as: | Name | Datentyp | |-----------------------------------|----------------| | Gravityforms_URL_Linkedin | URL | | Gravityforms_kurs/webinar_zeitpunkt | Datum & Zeit | | Gravityforms_kurs/webinar_bewertung | Dezimalzahl | | Gravityforms_feedback | Absatz | | Gravityforms_kontaktaufnahme | Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via Gravity Forms Submission: The workflow begins when a new form submission is received through the webhook. Transform Data for KlickTipp: Formats and validates raw form data for compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds processed data as a new subscriber or updates an existing one. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment Test the workflow by filling the form on Gravity Forms and verifying data updates in KlickTipp. Notes Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing. Resources: Gravity Forms KlickTipp Knowledge Base help article Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n
by Don Jayamaha Jr
This advanced agent analyzes long-term price action in the Binance Spot Market using 1-day candles. It calculates key macro indicators like RSI, MACD, BBANDS, EMA, SMA, and ADX to identify high-confidence trend setups and market momentum. Used by the Quant AI system for directional bias and macro-level signal validation. 🎥 Watch Tutorial: 🎯 Purpose Detect major trend reversals, consolidation zones, and macro bias Support long-term swing trading decisions Provide reliable 1-day signals for downstream agents 🧠 Core Features | Feature | Description | | --------------------------- | ------------------------------------------------------------ | | 🔁 Trigger | Called by parent workflows via Execute Workflow | | 📥 Input Format | { "message": "MATICUSDT", "sessionId": "telegram_id" } | | 📡 Webhook Call | Sends request to internal 1d indicators webhook | | 🧮 Technical Indicators | RSI, MACD, BBANDS, EMA, SMA, ADX (based on 40 daily candles) | | 🧠 GPT (gpt-4.1-mini) Agent | Interprets numerical data into human-readable trend signals | | 💬 Output | Summary suitable for Telegram or further agent consumption | 🔗 External Tools Called https://treasurium.app.n8n.cloud/webhook/1d-indicators Sends: { "symbol": "SOLUSDT" } 📊 Indicator Calculations | Indicator | Purpose | | -------------- | ------------------------------- | | RSI (14) | Overbought / Oversold Signals | | MACD (12,26,9) | Trend Reversals / Momentum | | BBANDS (20, 2) | Volatility Expansion | | EMA (20) | Short-Term Trend Confirmation | | SMA (20) | Macro-Level Support/Resistance | | ADX (14) | Trend Strength + Directional DI | 📦 Setup Import the JSON into n8n. Add your OpenAI API credentials. Ensure webhook /1d-indicators is connected and working. Use this agent as a sub-workflow in: Binance SM Financial Analyst Tool Binance Spot Market Quant AI Agent 📤 Output Example 📅 1D Overview – MATICUSDT • RSI: 71 → Overbought • MACD: Bearish Cross forming • BBANDS: Widening Volatility • EMA < SMA → Downtrend Momentum • ADX: 33 → High Trend Strength 📌 Notes Not user-facing — outputs are structured JSON or Telegram-style summaries. Pairs well with shorter timeframe tools (15m–4h) for confidence stacking. 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 Need help? Reach out on LinkedIn – Don Jayamaha
by Amjid Ali
Automate Digital Delivery After PayPal Purchase Using n8n A Complete Step-by-Step Guide to Seamless Template Delivery Built by Amjid Ali – SyncBricks Deliver personalized files instantly after PayPal transactions using n8n – without writing a single backend line. 🚀 What This n8n Workflow Does This automation template helps you automatically deliver a digital product (such as an n8n template or JSON file) to customers who pay via PayPal — within seconds. You can: Automatically extract customer info Identify what was purchased Send a clean, branded email with the product file Promote your other courses, books, and tools 📦 Use Case Example Product: AI-Powered Social Media Content Generator & Publisher When a customer buys this product through PayPal, this automation: Listens for a successful payment event Fetches order details via API Sends an HTML email with the template attached Promotes your other offerings with embedded links 🔧 Prerequisites You’ll need: An n8n instance (self-hosted or n8n Cloud) A PayPal developer account PayPal OAuth2 credentials configured in n8n Your product hosted as a downloadable .json file (Oracle, Dropbox, GitHub, etc.) SMTP email credentials in n8n 🧠 Step-by-Step Setup 1. Webhook Trigger Node: Webhook Listens for a POST request from PayPal’s webhook for PAYMENT.CAPTURE.COMPLETED events. 📌 Add the webhook to your PayPal Developer App > Webhooks. 2. Wait Node: Wait Adds a brief delay to ensure the payment is completely processed before continuing. 3. Filter Event Type Node: Switch Processes only when the event is PAYMENT.CAPTURE.COMPLETED. 4. Fetch Order Details Node: HTTP Request Retrieves the order information from PayPal's Orders API. URL format: https://api.paypal.com/v2/checkout/orders/{{ order_id }} 5. Extract Email & Product Info Node: Set Extracts first name, last name, email address, and the purchased item name. 6. Identify Product Purchased Node: Switch Checks if the product is “AI-Powered Social Media Content Generator & Publisher”. 7. Download Workflow File Node: HTTP Request Fetches the hosted workflow JSON from object storage (Oracle in this case). 8. Convert to Downloadable File Node: Code Converts the JSON content into a binary file and attaches it. 9. Send Custom Email Node: Send Email Sends a rich HTML email to the buyer with: Their name The file attachment Product name Helpful resource links: 📘 Mastering n8n Course on Udemy 📖 Step-by-Step Guide (n8n Book) 🎓 n8n Video Tutorials (Free Course) ☁️ Sign up for n8n Cloud – Use code AMJID10 🎥 YouTube Video Walkthrough 📚 Additional Learning Resources 🚀 My Full Automation Suite Explore more and master n8n with these resources: 🎓 Mastering n8n (Full Udemy Course) 📕 Get Your Step-by-Step Guide (n8n Book) 🎥 Get Step-by-Step Tutorials (Video Course) ☁️ Sign up for n8n Cloud 💡 Templates, Tools, and More 📺 YouTube Channel – SyncBricks 🙋 Need Help or Customization? Reach out! Email: amjid@amjidali.com LinkedIn: linkedin.com/in/amjidali Website: syncbricks.com
by Teddy
Webhook | Paper Summarization Who is this for? This workflow is designed for researchers, students, and professionals who frequently read academic papers and need concise summaries. It is useful for anyone who wants to quickly extract key information from research papers hosted on arXiv. What problem is this workflow solving? Academic papers are often lengthy and complex, making it time-consuming to extract essential insights. This workflow automates the process of retrieving, processing, and summarizing research papers, allowing users to focus on key findings without manually reading the entire paper. What this workflow does This workflow extracts the content of an arXiv research paper, processes its abstract and main sections, and generates a structured summary. It provides a well-organized output containing the Abstract Overview, Introduction, Results, and Conclusion, ensuring that users receive critical information in a concise format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Configure an external trigger using the Webhook node to accept paper IDs. Test the workflow by providing an arXiv paper ID. (Optional) Modify the summarization model or output format according to your preferences. How to customize this workflow to your needs Adjust the HTTPRequest node to fetch papers from other sources beyond arXiv. Modify the Summarization Chain node to refine the summary output. Enhance the Reorganize Paper Summary step by integrating additional language models. Add an email or Slack notification step to receive summaries directly. Workflow Steps Webhook receives a request with an arXiv paper ID. Send an HTTP request using "Request to Paper Page" to fetch the HTML content of the paper. Extract the abstract and sections using "Extract Contents". Split out all sections using "Split out All Sections" to process individual paragraphs. Clean up text using "Remove useless links" to remove unnecessary elements. Summarize extracted content using "Summarization Chain". Aggregate summarized content using "Aggregate summarized content". Reorganize the paper summary into structured sections using "Reorganize Paper Summary". Extract key information using "Content Extractor" to classify data into Abstract Overview, Introduction, Results, and Conclusion. Respond to the webhook with the structured summary. Note: This workflow is designed for use with arXiv research papers but can be adapted to process papers from other sources.
by Ranjan Dailata
Who this is for? Extract & Summarize Indeed Company Info is an automated workflow that extracts the Indeed company profile information using Bright Data Web Unlocker, transform it 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 looking to assess companies quickly during talent sourcing. Job seekers researching potential employers and needing summarized company insights. Market researchers and analysts monitoring competitor or industry players. What problem is this workflow solving? Searching and evaluating company profiles on Indeed manually can be time-consuming and inefficient, especially when dealing with large volumes of companies. Manually browsing, copying, and summarizing company descriptions, reviews, and ratings from Indeed hinders productivity and limits real-time insights. This workflow solves this by: Automating the extraction of company details from Indeed using Bright Data Web Unlocker. Summarizing the raw data using Google Gemini's language model for a quick, human-readable overview. Sending the transformed response with the summary to a chosen endpoint, like Slack, Notion, Airtable, or a custom webhook. What this workflow does This automated pipeline does the following: Scrape Indeed company profile pages (e.g., ratings, description, reviews) using Bright Data’s Web Unlocker. Transform the scraped content into structured JSON using n8n’s built-in tools. Summarize and extract meaningful insights using Google Gemini's large language model. Forward the summarized data to a specified webhook or app for real-time access, storage, or analysis. Forward the formatted response to a specified webhook or app for real-time access, storage, or analysis. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the search query, Bright Data zone by navigating to the Set Indeed Search Query node. 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: Changing the data source**: Replace the Indeed search input with other job or business listing platforms if needed (e.g., Glassdoor, Crunchbase) Refining the LLM prompt**: Tailor the Gemini prompt to transform or summarize the Indeed company information in a specific format. Routing the output to different destinations**: Send summaries or transformed response to Google Sheets, Airtable, or CRMs like HubSpot or Salesforce etc.
by Tharwat Mohamed
Document-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs 📝Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. ⚙️ How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > 💡Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. 🧰 Set up steps Connect your WhatsApp Cloud API account (Meta) Add your Google account and grant access to the Doc containing your company info Choose your AI model (ChatGPT/OpenAI or Gemini) Paste your document ID into the Google Docs node Connect your WhatsApp webhook to Meta (only takes 5 minutes) Done — start receiving and answering customer questions! > 📄 Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. 🔄 Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs 🤝 Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… 📩 I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236
by explorium
HubSpot Contact Enrichment with Explorium Template Download the following json file and import it to a new n8n workflow: hubspot\_flow.json Overview This n8n workflow monitors your HubSpot instance for newly created contacts and automatically enriches them with additional contact information. When a contact is created, the workflow: Detects the new contact via HubSpot webhook trigger Retrieves recent contact details from HubSpot Matches the contact against Explorium's database using name, company, and email Enriches the contact with professional emails and phone numbers Updates the HubSpot contact record with discovered information This automation ensures your sales and marketing teams have complete contact information, improving outreach success rates and data quality. Key Features Real-time Webhook Trigger**: Instantly processes new contacts as they're created Intelligent Matching**: Uses multiple data points (name, company, email) for accurate matching Comprehensive Enrichment**: Adds both professional and work emails, plus phone numbers Batch Processing**: Efficiently handles multiple contacts to optimize API usage Smart Data Mapping**: Intelligently maps multiple emails and phone numbers Profile Enrichment**: Optional additional enrichment for deeper contact insights Error Resilience**: Continues processing other contacts if some fail to match Prerequisites Before setting up this workflow, ensure you have: n8n instance (self-hosted or cloud) HubSpot account with: Developer API access (for webhooks) Private App or OAuth2 app created Contact object permissions (read/write) Explorium API credentials (Bearer token) - Get explorium api key Understanding of HubSpot contact properties HubSpot Requirements Required Contact Properties The workflow uses these HubSpot contact properties: firstname - Contact's first name lastname - Contact's last name company - Associated company name email - Primary email (read and updated) work_email - Work email (updated by workflow) phone - Phone number (updated by workflow) API Access Setup Create a Private App in HubSpot: Navigate to Settings → Integrations → Private Apps Create new app with Contact read/write scopes Copy the Access Token Set up Webhooks (for Developer API): Create app in HubSpot Developers portal Configure webhook for contact.creation events Note the App ID and Developer API Key Custom Properties (Optional) Consider creating custom properties for: Multiple email addresses Mobile vs. office phone numbers Data enrichment timestamps Match confidence scores Installation & Setup Step 1: Import the Workflow Copy the workflow JSON from the template In n8n: Navigate to Workflows → Add Workflow → Import from File Paste the JSON and click Import Step 2: Configure HubSpot Developer API (Webhook) Click on the HubSpot Trigger node Under Credentials, click Create New Enter your HubSpot Developer credentials: App ID: From your HubSpot app Developer API Key: From your developer account Client Secret: From your app settings Save as "HubSpot Developer account" Step 3: Configure HubSpot App Token Click on the HubSpot Recently Created node Under Credentials, click Create New (App Token) Enter your Private App access token Save as "HubSpot App Token account" Apply the same credentials to the Update HubSpot node Step 4: Configure Explorium API Credentials Click on the Explorium Match Prospects node Under Credentials, click Create New (HTTP Header Auth) Configure the authentication: Name: Authorization Value: Bearer YOUR_EXPLORIUM_API_TOKEN Save as "Header Auth Connection" Apply to all Explorium nodes: Explorium Enrich Contacts Information Explorium Enrich Profiles Step 5: Configure Webhook Subscription In HubSpot Developers portal: Go to your app's webhook settings Add subscription for contact.creation events Set the target URL from the HubSpot Trigger node Activate the subscription Step 6: Activate the Workflow Save the workflow Toggle the Active switch to ON The webhook is now listening for new contacts Node Descriptions HubSpot Trigger: Webhook that fires when new contacts are created HubSpot Recently Created: Fetches details of recently created contacts Loop Over Items: Processes contacts in batches of 6 Explorium Match Prospects: Finds matching person in Explorium database Filter: Validates successful matches Extract Prospect IDs: Collects matched prospect identifiers Enrich Contacts Information: Fetches emails and phone numbers Enrich Profiles: Gets additional profile data (optional) Merge: Combines all enrichment results Split Out: Separates individual enriched records Update HubSpot: Updates contact with new information Data Mapping Logic The workflow maps Explorium data to HubSpot properties: | Explorium Data | HubSpot Property | Notes | | ------------------------------ | ------------------ | ----------------------------- | | professions_email | email | Primary professional email | | emails[].address | work_email | All email addresses joined | | phone_numbers[].phone_number | phone | All phones joined with commas | | mobile_phone | phone (fallback) | Used if no other phones found | Data Processing The workflow handles complex data scenarios: Multiple emails**: Joins all discovered emails with commas Phone numbers**: Combines all phone numbers into a single field Missing data**: Uses "null" as placeholder for empty fields Name parsing**: Cleans sample data and special characters Usage & Operation Automatic Processing Once activated: Every new contact triggers the webhook immediately Contact is enriched within seconds HubSpot record is updated automatically Process repeats for each new contact Manual Testing To test the workflow: Use the pinned test data in the HubSpot Trigger node, or Create a test contact in HubSpot Monitor the execution in n8n Verify the contact was updated in HubSpot Monitoring Performance Track workflow health: Go to Executions in n8n Filter by this workflow Monitor success rates Review any failed executions Check webhook delivery in HubSpot Troubleshooting Common Issues Webhook not triggering Verify webhook subscription is active in HubSpot Check the webhook URL is correct and accessible Ensure workflow is activated in n8n Test webhook delivery in HubSpot developers portal Contacts not matching Verify contact has firstname, lastname, and company Check for typos or abbreviations in company names Some individuals may not be in Explorium's database Email matching improves accuracy significantly Updates failing in HubSpot Check API token has contact write permissions Verify property names exist in HubSpot Ensure rate limits haven't been exceeded Check for validation rules on properties Missing enrichment data Not all prospects have all data types Phone numbers may be less available than emails Profile enrichment is optional and may not always return data Error Handling Built-in error resilience: Failed matches don't block other contacts Each batch processes independently Partial enrichment is possible All errors are logged for review Debugging Tips Check webhook logs: HubSpot shows delivery attempts Review executions: n8n logs show detailed error messages Test with pinned data: Use the sample data for isolated testing Verify API responses: Check Explorium API returns expected data Best Practices Data Quality Complete contact records: Ensure name and company are populated Standardize company names: Use official names, not abbreviations Include existing emails: Improves match accuracy Regular data hygiene: Clean up test and invalid contacts Performance Optimization Batch size: 6 is optimal for rate limits Webhook reliability: Monitor delivery success API quotas: Track usage in both platforms Execution history: Regularly clean old executions Compliance & Privacy GDPR compliance: Ensure lawful basis for enrichment Data minimization: Only enrich necessary fields Access controls: Limit who can modify enriched data Audit trail: Document enrichment for compliance Customization Options Additional Enrichment Extend with more Explorium data: Job titles and departments Social media profiles Professional experience Skills and interests Company information Enhanced Processing Add workflow logic for: Lead scoring based on enrichment Routing based on data quality Notifications for high-value matches Custom field mapping Integration Extensions Connect to other systems: Sync enriched data to CRM Trigger marketing automation Update data warehouse Send notifications to Slack API Considerations HubSpot Limits API calls**: Monitor daily limits Webhook payload**: Max 200 contacts per trigger Rate limits**: 100 requests per 10 seconds Property limits**: Max 1000 custom properties Explorium Limits Match API**: Batched for efficiency Enrichment calls**: Two parallel enrichments Rate limits**: Based on your plan Data freshness**: Real-time matching Architecture Considerations This workflow integrates with: HubSpot workflows and automation Marketing campaigns and sequences Sales engagement tools Reporting and analytics Other enrichment services Security Best Practices Webhook validation**: Verify requests are from HubSpot Token security**: Rotate API tokens regularly Access control**: Limit workflow modifications Data encryption**: All API calls use HTTPS Audit logging**: Track all enrichments Advanced Configuration Custom Field Mapping Modify the Update HubSpot node to map to custom properties: // Example custom mapping { "custom_mobile": "{{ $json.data.mobile_phone }}", "custom_linkedin": "{{ $json.data.linkedin_url }}", "enrichment_date": "{{ $now.toISO() }}" } Conditional Processing Add logic to process only certain contacts: Filter by contact source Check for specific properties Validate email domains Exclude test contacts Support Resources For assistance: n8n issues**: Check n8n documentation and forums HubSpot API**: Reference HubSpot developers documentation Explorium API**: Contact Explorium support Webhook issues**: Use HubSpot webhook testing tools