Automated GC data profiling software

Chromatograms from any gas chromatography instrument are interpreted by our proprietary automated volatile organic compound fingerprinting pipeline — from raw signal to a trained classification model, with no manual peak picking.

Gas chromatography data is only as useful as the analysis behind it. Traditionally, turning raw chromatograms into answers means hours of manual peak integration and expert interpretation for every batch of samples — whatever instrument produced them. Our software is instrument-agnostic: it integrates with the gas chromatography hardware you already run, or connects to our own gas chromatograph Scout3, and automates the entire analysis workflow: it cleans the signal, detects and fits every peak, clusters and identifies peaks across samples, maps them to compounds, benchmarks five proprietary normalisation algorithms, and trains and evaluates classification models — all in one repeatable pipeline.

The pipeline: from instrument to trained model

Instrument integrationStep 1
  • 1Integration with your gas chromatography instrumentation — or connection to our own gas chromatograph, Scout3
Signal preparationSteps 2–6
  • 2Select samples
  • 3Load chromatograms
  • 4Smooth chromatograms
  • 5Remove baseline
  • 6Process sub-baselines
Peak detection & identificationSteps 7–11
  • 7Detect peaks
  • 8Fit peaks
  • 9Cluster peaks
  • 10Identify peaks
  • 11Identify compounds
NormalisationSteps 12–16
  • 12Normalisation algorithm 1
  • 13Normalisation algorithm 2
  • 14Normalisation algorithm 3
  • 15Normalisation algorithm 4
  • 16Normalisation algorithm 5
Machine learningSteps 17–19
  • 17Select peaks
  • 18Prepare training data
  • 19Model training & evaluation
Chromatogram with 20 automatically detected peaks, each labelled with its start, apex and end markers
Example of a chromatographic sample with 20 peaks automatically detected and identified (step 10 of the pipeline).

Why it matters

Consistent and repeatable. Every sample is processed the same way, every time — results do not depend on who ran the analysis, and whole measurement campaigns can be re-processed in minutes when the method evolves.

From peaks to answers. The pipeline does not stop at peak tables. Identified compounds become fingerprints, and fingerprints become trained, evaluated classification models — ready to sort samples, flag quality outliers or track a process in production.

Robust by design. Five proprietary normalisation algorithms are benchmarked automatically against each other, so each application ships with the preprocessing that genuinely performs best on its data.

The software powers every Scout3 deployment and every case study on this site — and it profiles chromatograms from any GC instrument, not just our own. Interested in what it could do with your chromatography data?