HumationHuman + Automation
Back to Catalog

Automate employee birthdays & work anniversaries with Google Gemini and Slack

Roshan RamaniRoshan Ramani
173 views
2/3/2026
GitHubRelease NotesAutomationMilestoneIssues
Official Page

Replace BillyBot: Free Slack Employee Birthday & Anniversary Automation

Who's it for

HR teams, team leaders, and operations managers looking to automate employee celebrations without expensive third-party tools like BillyBot. Perfect for startups to enterprise teams wanting to save $600-2,400+ annually while maintaining personalized, engaging employee recognition.

What it does

This workflow automatically monitors your employee database daily and posts AI-generated, unique celebration messages to Slack for birthdays and work anniversaries. Unlike generic bots, it creates personalized messages that never repeat, rotating through 12 different styles and tones to keep celebrations fresh and authentic.

How it works

  1. Daily Check: Runs every morning at 9 AM to scan your employee Google Sheet
  2. Smart Filtering: Matches today's date against employee birthdays and joining dates
  3. Data Aggregation: Collects all celebrating employees into a single payload
  4. AI Generation: Google Gemini creates unique, heartfelt messages with proper Slack formatting
  5. Auto-Post: Sends personalized celebrations directly to your chosen Slack channel

The AI ensures no two messages feel templated, calculating years of service for anniversaries and adapting tone based on tenure length.

Requirements

  • Google Sheets with employee data (columns: NO, Name, Email, Date of Birth, Joining Date in YYYY-MM-DD format)
  • Slack workspace with bot permissions to post messages
  • Google Gemini API key (free tier included)
  • n8n Cloud ($20/month) or self-hosted n8n (free)

Cost comparison: Save $600-2,400+ per year

BillyBot pricing: $1 per employee/month

  • 50 employees = $600/year
  • 100 employees = $1,200/year
  • 200 employees = $2,400/year

This solution: $0-20/month (unlimited employees)

  • Google Gemini API: FREE
  • Google Sheets API: FREE
  • Slack API: FREE
  • n8n: $20/month (Cloud) or $0 (self-hosted)

Your savings: 95-100% cost reduction regardless of team size.

Setup instructions

  1. Create Google Sheet: Add columns: NO, Name, Email, Date of Birth, Joining Date (ensure dates are YYYY-MM-DD format)
  2. Connect Google Sheets: Authenticate your Google account in the "Get row(s) in sheet" node
  3. Set up Slack: Create a Slack bot with chat:write permission and add to your celebration channel
  4. Configure Gemini: Add your Google Gemini API key to the "Google Gemini Chat Model" node
  5. Adjust Schedule: Change trigger time in "Schedule Trigger" node (default: 9 AM daily)
  6. Select Channel: Update Slack channel in "Send a message" node to your desired celebration channel
  7. Test: Run workflow manually to verify messages post correctly

Customization options

  • Change celebration time: Modify the Schedule Trigger to any hour (e.g., 8 AM for morning celebrations)
  • Adjust message tone: Edit the AI Agent system prompt to match your company culture (formal, casual, playful)
  • Multi-channel posting: Duplicate the Slack node to post to multiple channels (e.g., company-wide + team-specific)
  • Add upcoming reminders: Modify the IF node to check for celebrations within 7 days
  • Include photos: Extend the workflow to pull employee photos from your HR system
  • Custom emoji styles: Update the AI prompt to use your organization's custom Slack emojis

Key features

  • 12 rotating message styles prevent repetition
  • Automatic tenure calculation for work anniversaries
  • Culturally inclusive and professional tone
  • Mobile-optimized message length (1-3 lines)
  • Slack markdown formatting for visual appeal
  • Scales infinitely without additional cost

Note: Ensure your Google Sheet date formats are consistent (YYYY-MM-DD) for accurate date matching. The workflow processes dates in MM-DD format to match across years automatically.

Automate Employee Birthdays & Work Anniversaries with Google Gemini and Slack

This n8n workflow automates the process of identifying upcoming employee birthdays and work anniversaries from a Google Sheet, generating personalized celebration messages using Google Gemini, and posting these messages to a Slack channel.

What it does

  1. Triggers on a Schedule: The workflow runs daily to check for upcoming events.
  2. Reads Employee Data: It fetches employee data (names, birth dates, hire dates) from a specified Google Sheet.
  3. Identifies Upcoming Events: It filters the data to find employees with birthdays or work anniversaries occurring within the next 7 days.
  4. Generates Personalized Messages: For each identified event, it uses Google Gemini to craft a unique and celebratory message.
  5. Posts to Slack: The generated messages are then posted to a designated Slack channel to celebrate the employee.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Google Sheets Account: A Google Sheets spreadsheet containing your employee data (names, birth dates, hire dates).
  • Google Gemini API Key: Access to the Google Gemini API for generating messages.
  • Slack Account: A Slack workspace and a channel where the celebration messages will be posted.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Google Sheets: Set up a Google Sheets credential to access your employee data spreadsheet. Ensure the service account or OAuth credentials have read access to the sheet.
    • Google Gemini: Configure a Google Gemini credential with your API key.
    • Slack: Set up a Slack credential. This typically involves creating a Slack App and granting it the necessary permissions to post messages to channels.
  3. Update Google Sheets Node (ID: 18):
    • Specify the Spreadsheet ID and Sheet Name where your employee data is located.
    • Ensure the columns for employee names, birth dates, and hire dates are correctly mapped in the node's configuration.
  4. Update AI Agent Node (ID: 1119):
    • Ensure the Google Gemini Chat Model (ID: 1262) is correctly configured within the AI Agent node.
    • Review and adjust the prompt to Google Gemini to tailor the celebration messages to your company culture.
  5. Update Slack Node (ID: 40):
    • Specify the Channel ID where the celebration messages should be posted.
    • Customize the message format if desired, using expressions to include the generated message from the AI Agent.
  6. Activate the Workflow: Once configured, activate the workflow. It will run daily according to the schedule trigger.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942