From 200 Papers to One Report: The Complete AI Literature Review Workflow in SciSpace

​In this hands-on session, we'll walk through a complete, end-to-end literature review workflow in SciSpace from your first search query to a finished, citation-backed report. No theory dumps, no vague promises. Just the actual workflow, demonstrated live.

​You'll see how to run a review two ways: the non-agentic approach, where you stay in the driver's seat and steer every step, and the agentic approach, where you let AI handle the heavy lifting of searching, screening, and synthesizing. We'll cover when each one makes sense — and how to combine them.

​What we'll cover:

• ​Building a smart search and finding the right papers fast (without missing the important ones)

• ​Non-agentic vs. agentic workflows — what's the difference, and which to use when

• ​Running a Systematic Literature Review (SLR) from screening to extraction

• ​Generating and refining a full report review you can actually trust

• ​Practical tips to keep your output rigorous, transparent, and citation-ready

​Who should attend:
Researchers, PhD students, R&D teams, and anyone who runs literature reviews and wants to do them faster without cutting corners on quality.