01
Align
Bring corresponding signals into alignment across samples.
The Metablify Technology
First Principles and AI Find and Amplify Real Mass Features
Metablify combines the first principles of physics with AI to align, pool, and amplify consistent signal across complex LC/MS datasets, so real mass features can be detected with confidence amid the noise.
How Metablify works
From Noisy LC/MS Data to Quantified Mass Features
Metablify analyzes complex LC/MS datasets as a whole, using information across samples to align signals and amplify what is real.
02
Pool
Pool information across samples to strengthen consistent signal.
03
Amplify
Make consistent signal more prominent relative to background noise.
Metablify output
Cleaner, aligned, quantified mass features.
A structured, dataset-wide view of mass features ready for downstream analysis.
The difference
See more of what is real in your data
Legacy workflows may recover only a subset of real mass features. Metablify reveals a broader set from the same LC/MS dataset.
Legacy WorkflowsMetablify
Built for scale
Built for Complex, Large-Scale LC/MS Data
LC/MS experiments are generating larger, noisier, and more complex datasets. Metablify was built to analyze these datasets as a whole, helping researchers work across more samples without losing sight of the signals that matter.
Thousands
Samples in one untargeted metabolomics experiment
versus
Hundreds
Reported ceiling of existing software
Big Data Creates Bigger Analytical Challenges
Large Datasets
Designed to work across large numbers of LC/MS samples as experiments scale.
Complex Signal
Built for datasets where real mass features can be difficult to distinguish from background noise and variation.
Dataset-Wide Analysis
Uses information across samples to create a clearer view of the experiment as a whole.
Ready to see more in your LC/MS data?
Bring us your samples, LC/MS data, or workflow challenge.
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