GXL@gxl_ai
Today we’re launching Sy — GXL’s system for agent-native search and synthesis over biomedical preprints.
Biomedical preprints are being published at a pace no research team can fully track. With tens of thousands appearing every few months, it’s increasingly difficult to stay current, connect findings across papers, and trace conclusions back to the original source.
We built Sy to help researchers do exactly that.
Sy helps researchers search, analyze, and synthesize biomedical preprints at scale with exact source traceability. Rather than reading one paper at a time, researchers can use Sy to reason across the literature as a whole.
Sy works through a virtual filesystem that mirrors code environments, making it natural for agents to navigate and analyze research materials. In internal benchmarks across full-text Q&A, idea novelty checking, and deep cross-paper synthesis, Sy was:
➡️ 1.6× more accurate
➡️ 2.4× faster
➡️ 3.6× cheaper
than MCP-based approaches.
Sy performs especially well for workflows like:
➡️ drafting review-style syntheses across a body of literature
➡️ tracing how a paper has been used in later work
➡️ identifying trends, disagreements, and emerging themes across hundreds of papers
We’re excited to make biomedical research more thorough, scalable, and accessible.
Try Sy: sy.gxl.ai
See here for more information about our approach: gxl.ai/post/biomedica…