Overview

Deepcell provides high-content single-cell analysis and sorting through its REM-I platform, which combines label-free imaging, microfluidics, and AI to profile cells by their shape and internal features. The system images cells in microfluidic channels, uses deep learning to interpret morphology and other high-dimensional signals, and can gently sort cells based on these readouts while collecting rich data. It differentiates itself by seamlessly integrating microfluidics with AI-driven, label-free phenotyping to deliver detailed, single-cell readouts without chemical labels. Its goal is to give researchers and pharma teams precise cellular phenotyping and sorting to speed up discovery and drug development with data-rich insights at the single-cell level.