Aqumin’s technology comprises two major components: the Blended Data Model (BDM) and the 3D Landscapes. Monitoring, analyzing, and ad hoc discovery has never been faster or easier.

Blended Data Model

This patented technology enables the user to input and analyze multiple related datasets concurrently. The data must be related through a common attribute. For example, an experiment may have RNA, protein, and flow cytometry that all relate to particular genes and samples; those genes may then relate to pathways. The data is blended and aggregated, computations such as p-value and fold change are computed, and available for queries. An existing analysis workflow can be automated such that adjustments to parameters and cutoffs result in immediate updates.

3D Landscapes

Traditional static charts lose a lot of information and context. Aqumin’s 3D Landscape technology was created to interpret massive data sets visually so that relational patterns can be instantly spotted - turning data into actionable information without losing context. The Landscapes interface with the BDM to display all the data, and allow the user to reconfigure it in real-time. Each individual data point may be individually inspected as the user flies through the presentation.


Automate workflow

Change a parameter or cutoff and see an immediate update to the analysis.

Fully Interactive

Drill up and down through data layers. Zoom, pan, rotate, and tilt landscapes to see your data in a new dimension.

Get Instant Answers

Display and interact with hundreds of thousands of entities, instantly. With all your data at your fingertips, you can rapidly create and modify your views and receive instant answers.

Multiple Data Sources

Import any sort of table data (e.g. CSV, XLS, VCF) or connect to APIs.

Multiple Parameter Analysis

Configure your Landscape with five different metrics relating to height, color, position, size, and organization. Adjust your parameters and see instant updates.

Exploratory Tool

Leverage your intuitive understanding of the biology or processes behind the data to know what is important and what is not.