Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 15 nodes and runs on Airtable events. Along the way it connects OpenAI Chat Model and Airtable.
How it runs
Trigger: On Airtable events.
- Check if Processed (If): checks a condition and branches into true / false
- Check if Review Exist (If): checks a condition and branches into true / false
- Normalize Review Payload (Edit Fields (Set)): sets or maps fields
- AI: Analyze Review Sentiment (Basic LLM Chain): sends a prompt to an LLM, with model: Analyze Review Sentiment; output parser: Parse AI Output (JSON Schema)
- Flatten AI Output (Edit Fields (Set)): sets or maps fields
- Combine AI Output with Review Data (Edit Fields (Set)): sets or maps fields
- Check AI Output Valid (If): checks a condition and branches into true / false
- Prepare Airtable Update (Edit Fields (Set)): sets or maps fields
- AI Failure Handler (Edit Fields (Set)): sets or maps fields
- Update Airtable Review Record (Airtable): uses Airtable
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.
Nodes used (8)
- OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Edit Fields (Set)
n8n-nodes-base.set - Airtable Trigger
n8n-nodes-base.airtableTrigger - No Operation, do nothing
n8n-nodes-base.noOp - If
n8n-nodes-base.if - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Airtable
n8n-nodes-base.airtable
From the author
🏩 Analyze hotel reviews with OpenAI and update sentiment in Airtable This workflow automatically analyzes hotel guest reviews using OpenAI and updates the sentiment, summary, and confidence score directly in Airtable. It helps hospitality teams monitor guest…