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Metabolomic data analysis using

emzing, AI-Powered Software

Unlock the full potential of your raw/LC-MS data

works in-browser/supports mzML files

01The platform

Four modules. One project.

Raw data exploration, data processing, and statistical analysis - all integrated in one place, eliminating the need for data transfer between tools.

All modules share a common project and storage layer, so a feature table curated in Decode opens in Stat or Flux with the metadata already wired.

see · discover

LC-MS raw data exploration

Interactive visualization of raw data files

  • TIC and XICs
  • Mass scans: Isotope pattern and MS/MS spectra on click
  • Session state persists – no reuploading files
Discover
03Try it

Explore reanalyzed datasets.

Pick any of these curated studies and it opens in different modules.

the vault

115+ public domain metabolomics datasets, reprocessed using the emzing workflow.

Every study in the emzing Vault repository has been reprocessed through the deep learning-enabled workflow, so you can compare across cohorts and conduct statistical analyses. Studies across sample types including human biofluids, tissue, plant material, microbial lysates, and spent media, focusing on bioprocessing, isotope labelling, biomarker discovery, and natural product search - and many more all in one place.

115+Projects
10,000+Samples
38,000+Annotated Features
Browse the Vault
Featured from the Vault
05The company

Built by Clarity Bio.

Our vision is to become the most intelligent and trusted platform for metabolomics data analysis by redefining how scientists interact with mass spectrometry data.

Founding principle

To simplify complex metabolomics workflows using AI-driven automation, enabling researchers to generate accurate, reproducible and scalable scientific insights

  • STUDY DESIGN

    Untargeted, targeted, and stable isotope tracing workflows scoped end-to-end.

  • UNTARGETED METABOLOMICS SERVICES

    Metabolite extraction from a range of sample types, data acquisition on HR-LC-MS with optimized methods and robust QC.

  • TARGETED PANELS

    TQ-LCMS and GC-MS panels and optimized workflows for analyte quantification.

  • DATA ANALYTICS

    Deep learning-enabled processing with emzing, curated feature tables, and statistics for deep biological insights.

  • MODELING

    Genome scale metabolic modeling and flux balance analysis, Predictive modeling.

06FAQ

Frequently asked Questions

Get Started

Individual researcher

Open a published project

Pick a MetaboLights dataset and start exploring in Discover.

Try a dataset
Lab

Book a scoping call

30 minutes with a metabolomics scientist to talk through your workflow.

Evaluating engineer

Read the method paper

The benchmarks and the training set for the Emzing model are all public.

Open ChemRxiv