Deep analysis of cell type and disease state.

Remoscope images millions of cells from unprocessed fluid and analyzes them in real time, hands-free, with zero sample preparation.

Consumable Ultrathin flow cell 10 µL, unprocessed, no preparation
Hardware Remoscope A 200 × 300 mm benchtop device
Data Every cell, imaged live 0 cells imaged (actual throughput!!)
Analysis Mapped by morphology Foundation-model embeddings, fine-tuned per task

THE PROBLEM

Cellular fluid analysis requires labor-intensive and skill-dependent workflows.

Across research, pharmaceutical, diagnostics, and clinical settings, the same bottleneck holds: sample prep, staining, manual microscopy, and specialist expertise.

Remoscope is one platform: a high throughput label-free imaging cytometer that classifies, counts, and learns from every cell it sees. It images millions of cells per sample without labels or sample preparation and analyzes morphology in real time. Models run on device, built for the lab, clinic, or field.

Remoscope

200 × 300 mm 35 Watts Edge compute

10 µL

sample

Zero sample preparation

label-free

2M cells

in 10 minutes

Hands free

fully automated

APPLICATIONS

Same hardware. Many samples.

P. falciparum-infected cells imaged by Remoscope — Malaria diagnostic

Small animal hematology imaged by Remoscope — Small animal hematology

HEK cells imaged by Remoscope — Cell state detection

Sickle cells imaged by Remoscope — Sickle cell disease detection

Sepsis sample imaged by Remoscope — Sepsis Diagnostic

Cerebrospinal fluid imaged by Remoscope — Cellular analysis of CSF

Blood cancer sample imaged by Remoscope — Blood cancer detection

White blood cells imaged by Remoscope — Immune cell activation assays

Hematological abnormality imaged by Remoscope — Blood abnormality detection

Every sample is classified label-free, in real time — on the same hardware.

Foundation models

A data engine for foundation models.

> 3,000,000,000

cells imaged — and counting

Every Remoscope generates standardized, labeled imaging data at scale. We build our own foundation models which are finetuned for specific tasks like cell counts, subtype classification, anomaly detection, and diagnostics.

Grad-CAM saliency map highlighting disease state features for sepsis classification — Disease state features

Per-cell classification with bounding boxes from the YOGO model — Cell classification

Instance segmentation mask overlay — Instance segmentation

IN PRACTICE

Built for the lab and the clinic.

The Remoscope is robust and repeatable, enabling both discovery and research-use-only clinical use.

CONTACT

Contact Us

Feel free to book a demo, initiate a collaboration, or fill out a pre-order form!

contact@realtimeimagingsystems.com

Pre-order → Watch mini doc →

Our Team

Biohub · UCSF · UC Berkeley · Stanford University · IDRC