Deepcell
AI-driven single cell analysis
About
Founded in 2017 in Menlo Park, California, Deepcell combines artificial intelligence with microfluidics for single-cell analysis and sorting. The platform uses deep learning and computer vision to analyze individual cells based on morphological features captured via high-resolution imaging, then physically sorts cells of interest. This enables researchers and clinicians to identify and isolate rare cell populations without traditional molecular markers or staining. Deepcell targets applications in oncology, immunology, and cell therapy manufacturing, where identifying specific cell types is critical.
Products
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REM-I platform
— AI-powered platform for label-free imaging, analysis, and enrichment of viable cells using high-dimensional single-cell morphology data.
Customer sectors: oncology researchers, drug discovery scientists, cell & gene therapy developers
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Human Foundation Model
— Self-supervised AI extracting high-dimensional morphology embeddings from single-cell images in real time without labels or training.
Customer sectors: cell biologists, AI researchers, single-cell analysts
Market research & competitive positioning
Source-backed TAM / SAM / SOM sizing, displacement analysis, and an interactive peer positioning map for Deepcell — available to members.
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