How I Built an Agentic AI Research Assistant in 30 Minutes
Last Updated on September 9, 2025 by Editorial Team
Author(s): Saleh Alkhalifa
Originally published on Towards AI.
A self-hostable, token-aware pipeline that ranks recent studies and returns concise, cited answers
We live in an era of overwhelming scientific output: millions of articles, preprints, and updates accumulate faster than any individual can read. Agentic AI offers a pragmatic answer, autonomous, tool-using systems that can plan searches, execute them against authoritative databases, and distill only the most relevant evidence. Instead of generic chat, the goal is disciplined inquiry: construct structured queries, fetch primary sources, extract study design and outcomes, and return a defensible synthesis with precise citations.
This article details the development of a research partner using n8n, a platform for automating API calls, which efficiently queries PubMed for biomedical literature. The author discusses the specific tools used in the project, such as ESearch, ESummary, and EFetch, highlighting how the system prioritizes recent and relevant studies. By synthesizing findings from multiple abstracts while maintaining citation integrity, this approach showcases the potential of agentic AI to streamline the research process in an era of overwhelming information.
Read the full blog for free on Medium.
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