CellEngine offers fast and reliable Cytometry Analysis with advanced visualization

Introducing CellEngine® software by CellCarta (explore our video overview)

Elevate your Data Analysis with our Advanced CellEngine software

Are you limited by software that is too slow, can’t handle big data, or lacks key features to help you meet the industry standards?

Our immunologists collaborated with our bioinformatics team to design a cloud-based cytometry analysis software called CellEngine.


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Rahil Z et al. J Clin Invest 2020;130(11):5800-5816.

CellEngine software Features: Unmatched Performance

Our software provides the fastest analysis, whether you have just a few tubes, dozens of 384-well plates, or multi-gigabyte FCS files.

The largest experiment analyzed in CellEngine to date included 30,000 FCS files.

With its astounding performance, CellEngine is uniquely capable of analyzing entire longitudinal studies spanning months or years in a single, coherent view.

CellEngine software: Easy and customized autogating

With our built-in supervised autogating tool, you can harness the power of machine-learning to automatically tailor your gates.

Gate positions can be adjusted in seconds by using a small set of manually gated files from your dataset. This allows autogating to be seamlessly used to supplement existing manual gating steps, thus saving time and allowing analysts to spend more time on data interpretation and analysis.

KSM- CellEngine software

Learn more about easy and customized autogating with Cellengine

CellEngine software Features: Advanced Charting and Visualizations

Our unique features facilitate the creation of bar and line charts, box plots, heatmaps, flow plot overlays, gating hierarchies, and dose-response curves, all exportable at high-resolution for use in publications and slides.

CellEngine makes it easy to analyze replicates and assess long-term instrument and assay performance.

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CellEngine software Features: Metadata-Driven Analysis

Annotate your FCS files with your experimental conditions (e.g. timepoint, donor ID, dosage, treatment group) using a familiar spreadsheet interface, then use those annotations to drive your gating and visualization workflows with speed and reduced risk of user error.

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CellEngine software Features: Interoperable and Compatible

Easily import experiments from other widely used cytometry software like BD FACSDivaTM and Cytobank.

CellEngine is compatible with FCS files from more than 45 different cytometers and over a dozen manufacturers. Analyses and results can be exported in a variety of standard formats.

CellEngine software Features: Safe and Secure

By using geo-redundant storage, we ensure the protection of your data against natural disasters and hardware failures. All data is encrypted in-flight and at-rest using strong ciphers.


CellEngine was built for the cloud.

All of your experiments are organized in one place, accessible from any Internet-connected computer and shareable with your coworkers and collaborators.

Additionally, you can easily run algorithms like t-SNE and UMAP on the latest computing hardware without having to install R or Python.

CellEngine software Features: Advanced API

CellEngine offers a fully featured API, making it possible to integrate with your LIMS, ELN or EMR and to conduct advanced analyses as part of bioinformatics pipelines.

We provide and support API toolkits for R and Python.

CellEngine software Features: Regulatory Compliance

CellEngine provides all the features required for use in 21 CFR 11-compliant environments.

We continuously validate the software with thousands of automated tests to ensure consistent results and performance.

CellEngine software Features: Tested by Immunologists

CellEngine is used daily by our team of immunologists and our developers work closely with our scientists to create the best analysis experience possible.

CellEngine software Features: Cited in peer-reviewed publications

Publications in Cell:
Rahim MK et al. Cell 2023;186(6):1127-1143.

Publication in The Journal of Quantitative Cell Science:
Fallahzadeh R et al. Cytometry 2021;12(1):2338. doi:10.1002/cyto.a.24709.

Publication in Science Advances:
Mayer A et al. Sci Adv. 2023;9(3): doi:10.1126/sciadv.add1166

Publication in Nature Medicine:
Padrón J. L et al. Nat Med. 2022;28:1167-1177; doi:10.1038/s41591-022-01829-9.

Publication in Clinical Cancer Research:
Mettu B. N et al. Clin Cancer Res. 2022;28(5):882-892; doi:10.1158/1078-0432.CCR-21-2780.

Publication in The Journal of Clinical Investigation (JCI):
Rahil Z et al. JCI 2020;130(11):5800-5816.


Visit our Science Hub for the complete list of publications.