Run AI employee onboarding with Groq, Google Workspace, and Gemini
Ready for 3.0What this workflow does
This AI workflow has 62 nodes and runs manually, when you click “Execute workflow” (plus 5 other triggers). Along the way it connects Google Drive, Embeddings Google Gemini, Slack and Telegram and 3 more.
How it runs
Trigger: Manually, when you click “Execute workflow” (plus 5 other triggers).
- Load Docs Config (Edit Fields (Set)): sets or maps fields
- Normalize Input (Code): runs custom JavaScript code
- Orchestrator Config (Edit Fields (Set)): sets or maps fields
- Check-in Config (Edit Fields (Set)): sets or maps fields
- List Handbook Files (Google Drive): uses Google Drive
- Guard Input (If): checks a condition and branches into true / false
- Guard Hire (If): checks a condition and branches into true / false
- Read Tracking Sheet (Google Sheets): uses Google Sheets
- Download File (Google Drive): uses Google Drive
- Ingestion Failed Note (Edit Fields (Set)): sets or maps fields
…plus 32 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
- Still check Slack Trigger requires a signing secret on the Slack API credential (Slack Trigger (optional)).
Nodes used (25)
- Manual Trigger
n8n-nodes-base.manualTrigger - Edit Fields (Set)
n8n-nodes-base.set - Google Drive
n8n-nodes-base.googleDrive - Extract from File
n8n-nodes-base.extractFromFile - Simple Vector Store
@n8n/n8n-nodes-langchain.vectorStoreInMemory - Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Slack Trigger
n8n-nodes-base.slackTrigger - Telegram Trigger
n8n-nodes-base.telegramTrigger - Code
n8n-nodes-base.code - If
n8n-nodes-base.if - AI Agent
@n8n/n8n-nodes-langchain.agent - Groq Chat Model
@n8n/n8n-nodes-langchain.lmChatGroq - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Switch
n8n-nodes-base.switch - Slack
n8n-nodes-base.slack - Telegram
n8n-nodes-base.telegram - No Operation, do nothing
n8n-nodes-base.noOp - Google Sheets Trigger
n8n-nodes-base.googleSheetsTrigger - Google Sheets
n8n-nodes-base.googleSheets - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Gmail
n8n-nodes-base.gmail - Schedule Trigger
n8n-nodes-base.scheduleTrigger
From the author
Quick overview This workflow ingests onboarding documents from Google Drive into an in-memory vector store with Google Gemini embeddings, then runs a multi-channel onboarding chatbot powered by Groq, sends role-based welcome emails via Gmail when a new hire…