Open-source LC-MS data processing engine for simplifying metabolomics analysis


El-MAVEN is an open source mass spectrometry data processing engine that is optimal for isotopomer labeling and global metabolomic profiling experiments.

Process large datasets

Choose from a wide range of machine configurations to process large scale metabolomics.

Convert raw data with MSConvert

Convert raw data to commonly used mass spec data formats using command line/GUI tool hosted on Polly.

Maintain version control

Roll-back your computations to a previous state in an instant with restore analysis.

Group and visualize peaks

Visualize all peaks originating from the same ion feature as a single group on El-Maven. Track a metabolite across samples with a single visualization.

Minimize noise with automated peak detection

Go from raw data to curated peaks within minutes using Polly-Peak ML. Navigate large metabolomics datasets riddled with noisy ion features & correlate variations across cohorts.

Leverage built-in tools

Process LC-MS/MS data from liquid and gas chromatography based mass spec experiments. Perform targeted, untargeted and isotopomer labeling with a single tool.


Source Code
Origin Story



The birth of El-MAVEN can be traced back to another open source project, MAVEN, an open source LC-MS data processing engine developed by the Rabinowitz Lab at Princeton. We decided to use El-MAVEN as the working title for the project for few reasons. One, we wanted to acknowledge the original project. Secondly, El bears the stamp of Elucidata.


The inception and initial development of El-MAVEN would not have been possible without the unwavering support, constant feedback and financial support from Agios Pharmaceuticals Inc. Now, El-MAVEN is solely supported by and is constantly developing and adding new features based on the feedback of its loyal community.

About us

About Us

We are an MLOps company working at the intersection of technology and life sciences.

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Our team

Our team is small and nimble with multi-disciplinary individuals from varying backgrounds.

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Our mission

Breaking barriers in biomolecular research using a data-driven approach.

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