Visualize, segment, track, and classify your imaging data in hours, not weeks. Access state-of-the-art AI models on secure cloud GPUs. Forget about expensive infrastructure, Python scripts, and fragmented tools.
Stop cobbling together desktop software, notebooks, and scripts. CellWorkflow unifies visualization, segmentation, tracking, AI training, and quantitative analysis in one cloud-native pipeline — so every step is traceable and reproducible, from raw microscope file to quantified biological insight.
Explore 2D and 3D datasets in your browser — any device, any size. Navigate Z-stacks, time-lapses, and multi-channel data at terabyte scale, streamed directly from the cloud.
Automated 3D segmentation of tumor organoids, tumor cells, and individual T cells — with proofreading tools for edge cases. Replaces hand-drawn 3D surfaces and reconciliation across annotators.
Start with pre-trained segmentation models, or fine-tune them on your own data with a few clicks. No notebooks, no GPU provisioning — training runs in the cloud, progress updates live.
Share datasets with a link, invite annotators, and review results together. Export figure-ready outputs and link from your paper directly into the data — so readers can explore your findings.
One pipeline, versioned at every step. Upload the files your microscope already exports; get back segmentations, tracks, and quantified phenotypes — plus the figures and tables — that would have taken weeks to assemble by hand, all shareable with collaborators and reviewers at a link.
Your 3D time-lapse, in the formats your microscope already exports. Zeiss .czi, Leica .lif, Nikon .nd2, OME-TIFF, OME-Zarr — we handle conversion and storage in an automated pipeline that you only need to run once.
Segmentation, 3D tracking through division and death, and unsupervised classification. The full pipeline runs end-to-end on managed cloud GPUs — typically in hours, not the 2–4 weeks of manual execution.
Quantitative measurements, population signatures, per-track statistics, and exportable tables — plus publication-ready figures — ready to drop into a paper, a lab meeting, or a grant report.
Turn every segmented object and track into a quantitative phenotype — not just a count. Cluster cells by morphology, motility, intensity, or interaction, with confidence scores and editable labels. The example below: an immune-cell killing assay, phenotyped end-to-end with the BEHAV3D classifier.
Example — CAR-T against patient-derived colorectal organoid, replicate 03
From developmental biology to high-content screening to immuno-oncology, CellWorkflow replaces weeks of manual analysis with a repeatable, quantitative readout — at terabyte scale, without the infrastructure.
Follow cells through division, migration, and differentiation in developing embryos, organoids, and tissues. Maintain single-cell identity across long 3D time-lapses and quantify proliferation, fate, and movement — no manual frame-by-frame correction.
Segment and measure cells across plates and perturbation panels. Score morphology, intensity, and dynamics to rank hits — reproducibly, at terabyte scale, with the same pipeline applied identically to every well.
The platform's origin: classify how T cells engage and kill tumor organoids — serial killers, engagers, scanners, static — with the BEHAV3D classifier, to compare CAR-T, TCR-T, and TIL products by behavioral signature rather than endpoint killing alone.
Stop waiting months for the next model to reach your institution. We curate, benchmark, and package the latest open-source releases — MicroSAM, CellPose, StarDist, Trackastra, and more — ready to run on any dataset, on cloud GPUs we manage for you. Catalog is regularly refreshed.
Segment Anything, fine-tuned on light & electron microscopy. Interactive prompting with automatic instance segmentation across 2D, 3D, and time series.
Transformer-based cell tracking that links segmented instances across time — robust to division, death, and crowded co-culture conditions. Used to build the tracks that feed behavioral classification.
The lab workhorse. Generalist model for cells, nuclei, and organelles across brightfield, fluorescence, and phase — plus Human-in-the-Loop fine-tuning.
Foundation model for cell segmentation, trained on 1M+ annotated cells across tissue, imaging modalities, and species. Strong few-shot transfer.
Star-convex polygon detection — the gold standard for dense nuclei segmentation. Pre-trained for fluorescence, H&E, and 3D Z-stacks.
Unsupervised behavioral classifier for T cell–organoid co-cultures — the original BEHAV3D model from Alieva 2022 / Dekkers 2024. Recovers serial killers, super-engagers, scanners, and static cells from track features.
"The bottleneck was never the imaging — it was running the analysis. Weeks of manual work per experiment, stitched across desktop software, notebooks, and scripts. A cloud platform that productionizes the whole pipeline turns that into part of the experimental loop, not a quarterly project."
CellWorkflow exists because the original BEHAV3D authors wanted the pipeline they pioneered to be usable by every imaging lab — not just the ones that can dedicate a senior analyst to it for two to four weeks per dataset.
Group leader at the Princess Máxima Center for Pediatric Oncology, senior author of the BEHAV3D platform papers, and pioneer of 3D large-scale single-cell imaging of patient-derived organoids and immune co-cultures. Closely involved in shaping the platform's behavioral readouts.
First author of BEHAV3D: a 3D imaging-transcriptomics platform reveals heterogeneous cytotoxic T cell behaviors (Nature Biotechnology, 2022) and senior author of the BEHAV3D Nature Protocols paper (Dekkers et al., 2024). Established the behavioral phenotyping framework CellWorkflow productionizes.
CellWorkflow is built in collaboration with — but is independent from — the Princess Máxima Center and imAIgene Lab. Advisors do not endorse the platform's commercial claims.
Every plan includes the full viewer, annotation tools, and access to every model in the Hub. GPU credits and storage scale as your pipelines grow.
Fully managed on our infrastructure — the fastest way to get running. Your data stays encrypted, private by default, and never leaves the region you choose.
Upload one file from a recent experiment — any modality, any size. We'll run segmentation, tracking, and analysis end-to-end, and walk you through the results on a 30-minute call with a scientist, not a sales rep.