RamApp, a modern hyperspectral imaging toolbox for processing and analysis

An intuitive and user-friendly web application to explore Raman maps


Main Features

RamApp is a web application that aims to provide a user-friendly solution allowing researchers from various backgrounds to easily and successfully explore hyperspectral data, with a focus on Raman imaging


Import data obtained from different sources, including the most diffused commercial software


RamApp covers the most-used tools and techniques for Raman maps: from cropping and smoothing to spikes detection and baseline correction

Map analysis

Analyse Raman maps using statistical data analysis methods such as clustering, PCA, multivariate curve resolution (MCR) and N-FINDR

Stacked images composition

Create, as individual or stacked images, intensity maps with a high level of customization


Export publication-quality images or raw data for further analysis

User-friendly design

Interactively explore and visualise the data and the results of each processing step with a fast and easy work environment

Personal storage

Once uploaded, your data will be stored in a safe and personal space

Cloud-based solution

Access the app from any browser and operating system without requiring a local installation

Stay updated

News & events

Aug 31, 2023

RamApp at ICAVS12

RamApp was recently presented at the 12th International Conference on Advanced Vibrational Spectroscopy.

Jun 24, 2022

RamApp at SPEC 2022

We were thrilled to attend a conference in Dublin to show our most recent app development.


Project developers

Our Team

Meet The Team

Here are the main people who contributed to the development of RamApp.

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Renzo Vanna
Researcher @ CNR-IFN
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Giulia De Poli
Data scientist @ Datrix
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Andrea Masella
Data scientist @ Datrix
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Elia Broggio
Data scientist @ Datrix
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Dario Polli
Associate Professor @ Polimi
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Matteo Bregonzio
CTO @ Datrix

Citing RamApp

We are currently in the process of writing a paper that will detail the development and functionality of our application. Once this paper is published in a scientific journal, users will be able to cite the use of RamApp in their research, thereby increasing the visibility and recognition of our application in the academic community. This will also help to establish RamApp as a valuable tool for researchers in the field.


Any Questions? Answered

Don't hesitate to contact us if you have more questions

At the moment, RamApp can accept files from Renishaw™ grid map (*.wdf), Horiba™ LabSpec 5 (*.ngc), CSV tables (*.csv), Apache Parquet/Feather (*.parquet/*.feather), MATLAB™/Octave ( *.mat) and also custom-defined formats. We plan to extend the compatibility with other file formats in the next months according to the users needs.
Yes, you can export the processed hyperspectral cube as CSV tables (*.csv), Feather data frames (*.feather) or MATLAB™/Octave file (*.mat). In addition, you can export the entire RamApp project (*.zarr) which also includes the generated images and masks.
Currently RamApp is only available as an online web application because we believe that this approach has some advantages. For example it can be accessed from any platform, making it independent from the operative system. It is also easier to distribute and maintain: updates and bug fixes can be made easily and quickly, without the need for users to download and install anything.
As of today RamApp is supported by EU projects funds. In the future, we will consider alternative solutions such as donations or premium features to keep the project alive, but the current functionalities will always remain free for everyone.
The following features are already present on RamApp: map rotation, spatial and spectral crop, spatial and spectral smooth (denoising), cosmic rays detection and removal (despike), data resampling using a new spectral grid with equally-spaced nodes (helps to compare data having different calibration axes), data normalization, baseline correction, optical substrate identification and removal, cluster analysis, principal component analysis (PCA), multivariate curve resolution (MCR) and N-FINDR.
RamApp acts solely as a data processor, and the property of any uploaded data remains with you. If you choose to cancel the data from your personal space, we will promptly erase it from our servers. For further details, please refer to our Terms & Conditions (clause 8.4).

Ready to get started?

Start exploring the potential of RamApp now.


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