medium
n8n•Mar 16, 2026
Building an AI-Powered Research Automation System with n8n and Academic APIs
As a researcher, I struggled with manual literature review. This tutorial shows how to build an automated research pipeline using n8n, Groq, and academic APIs, reducing manual review time from six hours to five minutes.
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Original source
Key summary
This tutorial guides you through building an automated research pipeline using n8n that reduces manual literature review time from six hours to five minutes. The pipeline collects, normalizes, deduplicates, extracts structured data, scores relevance, and handles errors.
TL;DR
- Build an automated research pipeline using n8n
- Reduce manual literature review time from six hours to five minutes
- Collect, normalize, and deduplicate academic metadata
- Extract structured data using AI-powered LLM inference
- Score relevance and quality of research findings
- Handle errors and rate limits in academic APIs
- Use Groq API for high-speed LLM inference
- Leverage academic metadata providers for broad coverage
This content is automatically summarized using AI. For full context, always refer to the original article.
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