Templates / Summarize & extract Glassdoor company info with Google Gemini and Decodo

Summarize & extract Glassdoor company info with Google Gemini and Decodo

Needs changes

by Ranjan Dailata ✓ · 215 views · created 2025-10-20 · Market Research, AI Summarization

Needs changes. This template uses 1 thing(s) that n8n 3.0 removes: Function (legacy). 1 breaking item(s) found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 12 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Gemini Chat Model and Decodo (community).

How it runs

Trigger: Manually, when you click “Execute workflow”.

  1. Set the Input Fields (Edit Fields (Set)): sets 2 fields: company_url, geo
  2. Decodo: uses Decodo
  3. Structured Data Extractor (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model; output parser: Structured Output Parser
  4. Summarizer (Information Extractor): extracts structured fields from text with AI, with model: Google Gemini Chat Model
  5. Merge: merges the data from its input branches
  6. Format the Response (Code): runs custom JavaScript code
  7. Create a Binary Response (Function): runs custom JavaScript (legacy Function node)
  8. Read/Write Files from Disk: writes a file to disk

Services it uses

Google Gemini Chat ModelDecodo (community)

Before you upgrade to n8n 3.0

1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:

  • Function (legacy) in Create a Binary Response: replace with Code node, mode 'Run Once for All Items'.

Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).

Removed in 3.0Replace with
Function (legacy)
Create a Binary Response
Code node, mode 'Run Once for All Items'

Nodes used (11)

From the author

This workflow automates company research and intelligence extraction from Glassdoor using Decode API for data retrieval and Google Gemini for AI-powered summarization. Who this is for This workflow is ideal for: Recruiters, analysts, and market researchers…

Excerpt from Ranjan Dailata's description on n8n.io.

View the original on n8n.io → Check your own copy

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