This n8n workflow automates the logging and processing of Zoom attendance data. It is triggered via a webhook when attendance data is submitted, then processes the data through text splitting, embeddings creation, and vector storage. A conversational AI model (using Anthropic) analyzes the data, and the results are appended to a Google Sheet for record-keeping. In case of errors, a Slack alert notifies the user. This workflow is ideal for organizations managing large Zoom meetings needing automated attendance tracking, data analysis, and integrated updates.
Automated Zoom Attendance Logging Workflow
| Node Count | 11 – 20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatAnthropic, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreSupabase, googleSheets, slack, stickyNote, webhook |
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