Automate systematic literature reviews with Google Drive, GPT-4, Gemini, Qdrant and Airtable

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Built by Jannik Hiller Jannik Hiller
Created on June 09, 2026

Description

How it works
Automates systematic literature review by downloading papers from Google Drive, extracting text, and evaluating them against strict inclusion/exclusion criteria using LLM agents

Routes included papers to Qdrant vector stores with Gemini embeddings for semantic search, and excluded papers to a separate folder

Logs all decisions to Airtable with PRISMA-compliant justification for complete audit trails

Set up steps
Connect Google Drive credentials to access your paper folder

Configure Airtable base and table for decision logging

Add OpenAI (GPT-4) and Google Gemini API credentials for LLM evaluation and embeddings

Set up Qdrant instances for vector storage (supports up to 3 collections)

Keep detailed descriptions of your inclusion/exclusion criteria in the sticky notes inside your workflow

Nodes Used (10)

Airtable
n8n-nodes-base.airtable
Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm
Code
n8n-nodes-base.code
Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader
Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini
Google Drive
n8n-nodes-base.googleDrive
Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant
Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured