One merged peak
One mixed spectrum and a minor constituent missing from the report.
GC/MS software for fragrance analysis
Software for the people who have to be sure what is in the bottle.
Three local applications for essential-oil and fragrance laboratories: review raw Agilent GC/MS data, separate compounds merged into one peak, and compare a delivered lot with the materials you already approved.
From overlap to understandingOne signal.
One signal.
Three components.
Watch the components emerge from the curve.
AComponent BComponent CComponent
Reading the combined signal
Analyst v1.3.0IonUnweave v0.4.1IonConcord v0.8.0Runs entirely on your computer
01WHY IT EXISTSTHE MOTIVE
Built around the difficult sample
The software that ships with the instrument was never written for naturals.
Natural materials are crowded, variable, and full of overlapping constituents. A neat integration table can hide the exact trace component that explains authenticity, quality, or origin.
IonUnweave Systems focuses on three connected gaps: reviewing raw GC/MS evidence, separating what co-eluted, and comparing what changed after retention-time drift is accounted for.
Components separated
One fitted chromatographic component and reconstructed spectrum for each.
Differences explained
Matched, shifted, missing, and unexpected peaks shown separately.
02THE SOFTWARETHREE APPLICATIONS
A connected analytical workflow
Review the run.
Reveal what is there.
Then compare it properly.
Choose a product, then move through the briefing tabs. The interface is a concise overview; each product has a complete technical page.
PRODUCT BRIEFING0.4.1 · research preview
IonUnweave / Overview
Resolve what integration merges.
IonUnweave models the chromatographic shape instead. It fits overlapping regions as individual components, returns to the scan data, and reconstructs what each component contributed before searching each spectrum independently.
- Co-elution grouping
- Gaussian-mixture fitting
- Scan-level spectral extraction
From overlap to understandingOne signal.
One signal.
Three components.
Watch the components emerge from the curve.
AComponent BComponent CComponent
Reading the combined signal
03HOW WE BUILDTHREE COMMITMENTS
Trust is a product feature
Evidence stays visible.
Data stays with you.
01
Naturals first
Designed for the crowded chromatograms of essential oils, extracts, and complex fragrance materials—not idealized single-compound examples.
02
Local by default
No upload step, account, licence-server call, or telemetry. Raw data, libraries, and reference collections stay on your machine.
03
Nothing hidden
Every headline result opens into the peaks, settings, spectra, tolerances, and exceptions that produced it.
Local means local
Your library never leaves the bench.
All three applications process files on the workstation where they are installed. There is no cloud dependency, no server to provision, and no new acquisition method.
No account No telemetry No upload
04WHERE IT FITSAPPLICATIONS
One chromatogram, many questions
Built for the work laboratories already do.
01 / Quality control
Incoming raw-material verification
Review the source run, then compare a delivered lot with the approved reference and document every agreeing, shifted, missing, and unexpected peak.
IonUnweave AnalystIonConcord
02 / AuthenticityAdulteration & authenticity screening
Review spectral evidence, surface unexpected constituents, and recover trace markers that may be hidden beneath larger neighbours.
IonUnweave AnalystIonUnweaveIonConcord
03 / Sourcing & procurementSupplier qualification
Rank supplier samples against a house standard using the same tolerances, with the reasoning attached.
IonConcord
04 / Creation & developmentDeformulation & competitive analysis
Review each run in context, recover trace constituents from complex finished fragrances, and search reconstructed spectra independently.
IonUnweave AnalystIonUnweave
The useful first conversationBring us a
Bring us a
chromatogram.
Send a real dataset and the question you could not answer from it. We will show what each application would do—including where it would not help.
Start with your data