Live-cell imaging, AI inference, and smart sorting in one workflow
Deepcell redefines how biology is studied by giving science sight: the ability to see and enrich living cells in their full complexity, without labels or destructive prep. The REM-i platform turns raw morphology into a dynamic dataset, capturing rare cell states in real time and preserving them for deeper analysis. With high-throughput performance, live-cell precision, and the power of AI-driven discovery, it opens new frontiers in research and therapeutic development, making every experiment richer, faster, and more revealing.
Custom-designed flow dynamics provide stable, reproducible handling of delicate cells, ensuring consistent high-quality results.
Optimized shear forces and fluid control protect cell viability and morphology, enabling downstream assays, culture, or therapeutic use without compromise.
Capture subcellular structures and subtle morphological features in real time at 0.16 µm/pixel, revealing fine morphological detail revealing biology that traditional methods miss.
Image up to 1,000 cells per second. Store and visualize every cell image, making datasets easy to explore, present, and publish.
A self-supervised foundation model delivers real-time analysis of cell images, combining deep learning embeddings with computer vision morphometrics - no labels or markers required.
Pre-trained for broad applicability to human samples, REM-i’s AI is ready to use immediately, eliminating the need for custom training or setup.
AI-driven sorting classifies even rare cell types in real time, enriching multiple subpopulations while preserving viability for downstream use.
Designed for simplicity, REM-i integrates seamlessly into lab workflows, transforming complex samples into actionable datasets.
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