# JL_ai

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [Wonjun Lee](https://cerebralvalley.ai/u/won5830)
- **GitHub:** https://gitfront.io/r/won5830/GtUW7r6F9vSq/CytoAgent/
- **Demo video:** https://youtu.be/sVtfstlPftE
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/220

Flow cytometry underpins immunology and clinical diagnostics, yet its analysis is still bottlenecked by manual gating inside fragmented, subscription-locked GUIs like FlowJo and Cytobank. Unlike single-cell sequencing, cytometry data suffers from severe batch-to-batch variability and inconsistent marker panels, so conventionally trained models generalize poorly and expert manual gating stays unavoidable.
We built an AI-native framework that lets Claude take flow cytometry data end-to-end — reading an experiment's markers, formulating a gating and phenotyping strategy, executing it, and running downstream analysis to reach conclusions, all in one pipeline. At its core is a vision-language foundation model that performs marker-agnostic gating directly from text prompts, connected to cytometry tools through a Model Context Protocol (MCP) layer and extended via a plugin system that absorbs new methods as the field evolves.
This removes the single largest barrier in cytometry analysis: reliance on manual, non-reproducible gating locked inside closed software. By making the workflow automated, reproducible, and agent-driven, it lowers cost, accelerates immunology and diagnostics research, and turns a fragmented toolchain into a single, builder-friendly framework researchers can extend for their own experiments.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/220. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt