Categorize Revolut transactions automatically with GPT-4 and Supabase
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 14 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Drive, Supabase and OpenAI Chat Model.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Get many rows (Supabase): get many
- Aggregate: combines items into one
- Download extract (Google Drive): download
- Extract from File: extracts data from a file
- Normalize content (Edit Fields (Set)): sets 13 fields: type, product, started_date…
- Uniq Hash (Crypto): hashes or encrypts values
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- Extract merchant (Code): runs custom JavaScript code
- Category extraction (Basic LLM Chain): sends a prompt to an LLM, with model: gpt-4.1-mini; output parser: Output Parser
- Merge: merges the data from its input branches
…plus 1 more step. 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.
Nodes used (13)
- Manual Trigger
n8n-nodes-base.manualTrigger - Google Drive
n8n-nodes-base.googleDrive - Supabase
n8n-nodes-base.supabase - Edit Fields (Set)
n8n-nodes-base.set - Code
n8n-nodes-base.code - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Merge
n8n-nodes-base.merge - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Aggregate
n8n-nodes-base.aggregate - Crypto
n8n-nodes-base.crypto - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Extract from File
n8n-nodes-base.extractFromFile
From the author
Revolut Extracts Analyzer This n8n template processes Revolut statements, normalizes transactions, and uses AI to categorize expenses automatically. Use cases include detecting subscriptions, separating internal transfers, and building dashboards to track…