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Transcribing Bank Statements To Markdown Using Gemini Vision AI

n8n template #2421
This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditiona OCR because: It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to

How to set it up

  1. Open template #2421 on n8n.io and click Use for free, or copy the template JSON and paste it onto an empty canvas in n8n.
  2. Create 2 credentials under Credentials → Add credential: Google Drive, Google Gemini Chat Model. Then open each of those nodes and pick the credential.
  3. Check the model in the Google Gemini Chat Model node. The template may point at a model your account can't use; swap it for one you have access to.
  4. Click Execute workflow and step through each node's output to confirm the data looks right.
  5. Toggle the workflow to Active so its trigger runs on its own.

Hand off to your agent

Prompt

Help me set up the n8n workflow "Transcribing Bank Statements To Markdown Using Gemini Vision AI" (https://n8n.io/workflows/2421). It uses: Edit Image, HTTP Request, Google Drive, Compression, Code, Basic LLM Chain, Google Gemini Chat Model, Information Extractor. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.

Paste into Claude Code and it will do the rest.

Apps and nodes

Questions

Yes. Jimleuk published it free on n8n.io as a verified creator, and it has 15K views. It runs on n8n Cloud or a self-hosted n8n instance.

Google Drive, Google Gemini Chat Model. The other 6 nodes are built into n8n.

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