Extract and analyze Drive documents, organize them in Sheets
Workflow Description
An automation that retrieves documents from Google Drive, analyzes them with Gemini AI, removes duplicates, and automatically stores results in Google Sheets. Enables rapid review and searchability of large document collections.
How it works
- 1.Trigger automation manually or via HTTP request
- 2.Load documents from Google Drive and split into text chunks
- 3.Analyze and classify texts using Gemini, extract key information
- 4.Generate vector embeddings and store in Qdrant vector database
- 5.Remove duplicate records from results
- 6.Write clean data to Google Sheets for review
Use cases
- Process hundreds of legal documents and organize content in structured tables
- Analyze customer reports from Drive and auto-categorize by priority
- Monitor Twitter/X posts, extract insights, and document findings in Sheets
- Index large content collections and make them searchable via vector search
Requirements
- Connected Google accounts (Sheets, Drive, and Gemini API access)
- Source documents in Google Drive (text or PDF formats)
- Qdrant or external Vector Store configured for document embeddings
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (88)
When clicking ‘Test workflow’
Manual Trigger
Web Search For API Schema
HTTP Request
Scrape Webpage Contents
HTTP Request
Results to List
Split Out
Recursive Character Text Splitter1
Text Splitter Recursive Character Text Splitter
Content Chunking @ 50k Chars
Set
Split Out Chunks
Split Out
Default Data Loader
Document Default Data Loader
Set Embedding Variables
Set
Execute Workflow Trigger
Execute Workflow Trigger
Execution Data
Execution Data
EventRouter
Switch
Google Gemini Chat Model
Gemini Model
Successful Runs
Filter
For Each Document...
Split In Batches
Embeddings Google Gemini
Gemini Model
Has API Documentation?
If
Store Document Embeddings
Vector Store Qdrant
Embeddings Google Gemini1
Gemini Model
Google Gemini Chat Model1
Gemini Model
Extract API Operations
Information Extractor
Search in Relevant Docs
Vector Store Qdrant
Wait
Wait
Remove Dupes
Remove Duplicates
Filter Results
Filter
Research
Execute Workflow
Has Results?
If
Response Empty
Set
Response OK
Set
Combine Docs
Aggregate
Template to List
Split Out
Query Templates
Set
Google Gemini Chat Model2
Gemini Model
For Each Template...
Split In Batches
Query & Docs
Set
Identify Service Products
Information Extractor
Extract API Templates
Set
Embeddings Google Gemini2
Gemini Model
Search in Relevant Docs1
Vector Store Qdrant
Combine Docs1
Aggregate
Query & Docs1
Set
For Each Template...1
Split In Batches
Merge Lists
Code
Remove Duplicates
Remove Duplicates
Append Row
Google Sheets
Response OK1
Set
Has Operations?
If
Response Empty1
Set
Research Pending
Google Sheets
Research Result
Google Sheets
Research Error
Google Sheets
Extract Pending
Google Sheets
Research Event
Set
Extract Event
Set
Extract
Execute Workflow
Extract Result
Google Sheets
Extract Error
Google Sheets
Get API Operations
Google Sheets
Contruct JSON Schema
Code
Upload to Drive
Google Drive
Set Upload Fields
Set
Response OK2
Set
Generate Event
Set
Generate Pending
Google Sheets
Generate
Execute Workflow
Generate Error
Google Sheets
Generate Result
Google Sheets
Get All Extract
Google Sheets
Get All Research
Google Sheets
For Each Research...
Split In Batches
For Each Extract...
Split In Batches
Wait1
Wait
All Research Done?
If
All Extract Done?
If
Get All Generate
Google Sheets
All Generate Done?
If
For Each Generate...
Split In Batches
Wait2
Wait
Has Results?1
If
Response Scrape Error
Set
Has Results?3
If
Response No API Docs
Set
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Sticky Note3
Sticky Note
Sticky Note4
Sticky Note
Sticky Note5
Sticky Note