HumationHuman + Automation
Back to Catalog

Automate HR Q&A sessions with AI question clustering and Google Calendar integration

Gabriel SantosGabriel Santos
1924 views
2/3/2026
CheerioJSWeb ScrapingContent ExtractionUtilityHTTP Request
Official Page

This workflow helps HR teams run smoother monthly Q&A sessions with employees.

  • Who’s it for HR teams and managers who want to centralize employee questions, avoid duplicates, and keep meetings focused.

  • How it works

  1. Employees submit questions through a styled form.
  2. Questions are stored in a database.
  3. HR selects a date range to review collected questions.
  4. An AI Agent deduplicates and clusters similar questions, then generates a meeting script in Markdown format.
  5. The Agent automatically creates a Google Calendar event (with a Google Meet link) on the last Friday of the current month at 16:00–17:00.
  6. The script is returned as a downloadable .txt file for HR to guide the session.

  • Requirements

    • MySQL (or compatible DB) for storing questions
    • Google Calendar credentials
    • OpenAI (or another supported LLM provider)

  • How to customize

    • Adjust meeting day/time in the Set node expressions
    • Change database/table name in MySQL nodes
    • Modify clustering logic in the AI Agent prompt
    • Replace the form styling with your company’s branding

This template ensures no repeated questions, keeps HR better prepared with a structured script, and automates meeting scheduling in just one click.

Automate HR QA Sessions with AI Question Clustering and Google Calendar Integration

This n8n workflow streamlines the process of conducting HR Quality Assurance (QA) sessions. It leverages AI to cluster interview questions based on their similarity, generates a structured output, and then integrates with Google Calendar to schedule these sessions. The workflow is triggered by a form submission, making it easy for HR teams to initiate the QA process.

What it does

  1. Triggers on Form Submission: The workflow starts when an HR team member submits a form containing interview questions.
  2. Retrieves Interview Questions: It fetches the submitted interview questions, likely from a database (MySQL in this case).
  3. Applies AI Question Clustering: An AI agent, powered by an OpenAI Chat Model, processes the interview questions. It uses a structured output parser to cluster similar questions.
  4. Generates Structured Output: The AI outputs a structured JSON object containing the clustered questions, making them easy to manage and analyze.
  5. Converts to File (Optional/Placeholder): The structured output is then converted into a file format. This step might be a placeholder for future integration or for generating reports.
  6. Aggregates Data: The clustered and structured question data is aggregated, preparing it for further actions.
  7. Schedules Google Calendar Events: The aggregated data is used to create events in Google Calendar, effectively scheduling the HR QA sessions.
  8. Presents Form for Next Steps: After scheduling, a form is presented, potentially allowing the user to initiate further actions or confirm the session details.

Prerequisites/Requirements

  • n8n Instance: A running instance of n8n.
  • MySQL Database: Access to a MySQL database to store and retrieve interview questions.
  • OpenAI API Key: An API key for OpenAI to power the AI Chat Model and agent.
  • Google Calendar Account: A Google account with access to Google Calendar for scheduling events.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • MySQL: Set up your MySQL credentials to connect to your database.
    • OpenAI: Provide your OpenAI API key for the "OpenAI Chat Model" and "AI Agent" nodes.
    • Google Calendar: Configure your Google Calendar credentials to allow n8n to create events.
  3. Customize Form Trigger:
    • Access the "n8n Form Trigger" node and customize the form fields to match the input expected for interview questions.
  4. Adjust AI Logic (Optional):
    • Review the "AI Agent" and "Structured Output Parser" nodes. You might need to refine the prompts or parser schema to optimize question clustering for your specific needs.
  5. Configure Google Calendar:
    • In the Google Calendar node (not explicitly shown in JSON but implied by the directory name), configure the event details such as title, description, start/end times, and attendees, using the data processed by the AI.
  6. Activate the Workflow: Once configured, activate the workflow.
  7. Trigger the Workflow: Submit the n8n form to initiate the HR QA session automation.

Related Templates

Send WooCommerce discount coupons to customers via WhatsApp using Rapiwa API

Who is this for? This workflow is ideal for WooCommerce store owners who want to automatically send promotional WhatsApp messages to their customers when new coupons are created. It’s designed for marketers and eCommerce managers looking to boost engagement, streamline coupon sharing, and track campaign performance effortlessly through Google Sheets. Overview This workflow listens for WooCommerce coupon creation events (coupon.created) and uses customer billing data to send promotional WhatsApp messages via the Rapiwa API. The flow formats the coupon data, cleans phone numbers, verifies WhatsApp registration with Rapiwa, sends the promotional message when verified, and logs each attempt to Google Sheets (separate sheets for verified/sent and unverified/not sent). What this Workflow Does Listens for new coupon creation events in WooCommerce via the WooCommerce Trigger node Retrieves all customer data from the WooCommerce store Processes customers in batches to control throughput Cleans and formats customer phone numbers for WhatsApp Verifies if phone numbers are valid WhatsApp accounts using Rapiwa API Sends personalized WhatsApp messages with coupon details to verified numbers Logs all activities to Google Sheets for tracking and analysis Handles both verified and unverified numbers appropriately Key Features Automated coupon distribution: Triggers when new coupons are created in WooCommerce Customer data retrieval: Fetches all customer information from WooCommerce Phone number validation: Verifies WhatsApp numbers before sending messages Personalized messaging: Includes customer name and coupon details in messages Dual logging system: Tracks both successful and failed message attempts Rate limiting: Uses batching and wait nodes to prevent API overload Data formatting: Structures coupon information for consistent messaging Google Sheet Column Structure A Google Sheet formatted like this ➤ sample The workflow uses a Google Sheet with the following columns to track coupon distribution: | name | number | email | address1 | couponCode | couponTitle | couponType | couponAmount | createDate | expireDate | validity | status | | ----------- | ------------- | --------------------------------------------------- | --------- | ---------- | -------------- | ---------- | ------------ | ------------------- | ------------------- | ---------- | -------- | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur-DOHS | 62dhryst | eid offer 2025 | percent | 20.00 | 2025-09-11 06:08:02 | 2025-09-15 00:00:00 | unverified | not sent | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur-DOHS | 62dhryst | eid offer 2025 | percent | 20.00 | 2025-09-11 06:08:02 | 2025-09-15 00:00:00 | verified | sent | Requirements n8n instance with the following nodes: WooCommerce Trigger, Code, SplitInBatches, HTTP Request, IF, Google Sheets, Wait WooCommerce store with API access Rapiwa account with API access for WhatsApp verification and messaging Google account with Sheets access Customer phone numbers in WooCommerce (stored in billing.phone field) Important Notes Phone Number Format: The workflow cleans phone numbers by removing all non-digit characters. Ensure your WooCommerce phone numbers are in a compatible format. API Rate Limits: Rapiwa and WooCommerce APIs have rate limits. Adjust batch sizes and wait times accordingly. Data Privacy: Ensure compliance with data protection regulations when sending marketing messages. Error Handling: The workflow logs unverified numbers but doesn't have extensive error handling. Consider adding error notifications for failed API calls. Message Content: The current message template references the first coupon only (coupons[0]). Adjust if you need to handle multiple coupons. Useful Links Dashboard: https://app.rapiwa.com Official Website: https://rapiwa.com Documentation: https://docs.rapiwa.com Support & Help WhatsApp: Chat on WhatsApp Discord: SpaGreen Community Facebook Group: SpaGreen Support Website: https://spagreen.net Developer Portfolio: Codecanyon SpaGreen

RapiwaBy Rapiwa
110

Generate Weather-Based Date Itineraries with Google Places, OpenRouter AI, and Slack

🧩 What this template does This workflow builds a 120-minute local date course around your starting point by querying Google Places for nearby spots, selecting the top candidates, fetching real-time weather data, letting an AI generate a matching emoji, and drafting a friendly itinerary summary with an LLM in both English and Japanese. It then posts the full bilingual plan with a walking route link and weather emoji to Slack. 👥 Who it’s for Makers and teams who want a plug-and-play bilingual local itinerary generator with weather awareness — no custom code required. ⚙️ How it works Trigger – Manual (or schedule/webhook). Discovery – Google Places nearby search within a configurable radius. Selection – Rank by rating and pick the top 3. Weather – Fetch current weather (via OpenWeatherMap). Emoji – Use an AI model to match the weather with an emoji 🌤️. Planning – An LLM writes the itinerary in Markdown (JP + EN). Route – Compose a Google Maps walking route URL. Share – Post the bilingual itinerary, route link, and weather emoji to Slack. 🧰 Requirements n8n (Cloud or self-hosted) Google Maps Platform (Places API) OpenWeatherMap API key Slack Bot (chat:write) LLM provider (e.g., OpenRouter or DeepL for translation) 🚀 Setup (quick) Open Set → Fields: Config and fill in coords/radius/time limit. Connect Credentials for Google, OpenWeatherMap, Slack, and your LLM. Test the workflow and confirm the bilingual plan + weather emoji appear in Slack. 🛠 Customize Adjust ranking filters (type, min rating). Modify translation settings (target language or tone). Change output layout (side-by-side vs separated). Tune emoji logic or travel mode. Add error handling, retries, or logging for production use.

nodaBy noda
52

Competitor intelligence agent: SERP monitoring + summary with Thordata + OpenAI

Who this is for? This workflow is designed for: Marketing analysts, SEO specialists, and content strategists who want automated intelligence on their online competitors. Growth teams that need quick insights from SERP (Search Engine Results Pages) without manual data scraping. Agencies managing multiple clients’ SEO presence and tracking competitive positioning in real-time. What problem is this workflow solving? Manual competitor research is time-consuming, fragmented, and often lacks actionable insights. This workflow automates the entire process by: Fetching SERP results from multiple search engines (Google, Bing, Yandex, DuckDuckGo) using Thordata’s Scraper API. Using OpenAI GPT-4.1-mini to analyze, summarize, and extract keyword opportunities, topic clusters, and competitor weaknesses. Producing structured, JSON-based insights ready for dashboards or reports. Essentially, it transforms raw SERP data into strategic marketing intelligence — saving hours of research time. What this workflow does Here’s a step-by-step overview of how the workflow operates: Step 1: Manual Trigger Initiates the process on demand when you click “Execute Workflow.” Step 2: Set the Input Query The “Set Input Fields” node defines your search query, such as: > “Top SEO strategies for e-commerce in 2025” Step 3: Multi-Engine SERP Fetching Four HTTP request tools send the query to Thordata Scraper API to retrieve results from: Google Bing Yandex DuckDuckGo Each uses Bearer Authentication configured via “Thordata SERP Bearer Auth Account.” Step 4: AI Agent Processing The LangChain AI Agent orchestrates the data flow, combining inputs and preparing them for structured analysis. Step 5: SEO Analysis The SEO Analyst node (powered by GPT-4.1-mini) parses SERP results into a structured schema, extracting: Competitor domains Page titles & content types Ranking positions Keyword overlaps Traffic share estimations Strengths and weaknesses Step 6: Summarization The Summarize the content node distills complex data into a concise executive summary using GPT-4.1-mini. Step 7: Keyword & Topic Extraction The Keyword and Topic Analysis node extracts: Primary and secondary keywords Topic clusters and content gaps SEO strength scores Competitor insights Step 8: Output Formatting The Structured Output Parser ensures results are clean, validated JSON objects for further integration (e.g., Google Sheets, Notion, or dashboards). Setup Prerequisites n8n Cloud or Self-Hosted instance Thordata Scraper API Key (for SERP data retrieval) OpenAI API Key (for GPT-based reasoning) Setup Steps Add Credentials Go to Credentials → Add New → HTTP Bearer Auth* → Paste your Thordata API token. Add OpenAI API Credentials* for the GPT model. Import the Workflow Copy the provided JSON or upload it into your n8n instance. Set Input In the “Set the Input Fields” node, replace the example query with your desired topic, e.g.: “Google Search for Top SEO strategies for e-commerce in 2025” Execute Click “Execute Workflow” to run the analysis. How to customize this workflow to your needs Modify Search Query Change the search_query variable in the Set Node to any target keyword or topic. Change AI Model In the OpenAI Chat Model nodes, you can switch from gpt-4.1-mini to another model for better quality or lower cost. Extend Analysis Edit the JSON schema in the “Information Extractor” nodes to include: Sentiment analysis of top pages SERP volatility metrics Content freshness indicators Export Results Connect the output to: Google Sheets / Airtable for analytics Notion / Slack for team reporting Webhook / Database for automated storage Summary This workflow creates an AI-powered Competitor Intelligence System inside n8n by blending: Real-time SERP scraping (Thordata) Automated AI reasoning (OpenAI GPT-4.1-mini) Structured data extraction (LangChain Information Extractors)

Ranjan DailataBy Ranjan Dailata
632