Aurora
At HexTech Research s.r.o., our primary focus is the development of a platform called Aurora, specifically designed for researchers. Aurora accelerates the evaluation of research by automating the processing of experimental data through AI-powered image recognition. In addition, it offers extensive data storage capacity. This dual functionality supports researchers by streamlining data management and enhancing the speed and accuracy of their analyses.
Our current AI model is capable of independently identifying objects of interest, segregating them, categorizing them into a database that it also self-creates, and analyzing them.
Take the following example: the model identifies and separates Petri dishes from the background. It also identifies and segregates microorganisms within those dishes. The process concludes by measuring them in relation to the size of the Agar and counting the number of colonies present in the dish. Both of these pieces of information are critical for determining the success of an experiment. However, obtaining this data manually can be time-consuming, expensive, and prone to inaccuracies. This is where Aurora, with its automation capabilities, becomes invaluable.
The same model used in the previous example was also applied to experimental data from gel electrophoresis. The study aimed to separate proteins using an electric current and then evaluate them by integrating the intensity of each blue mark in the samples.
Remarkably, our model successfully evaluated all samples without the need to significantly alter the settings, despite the substantial differences in the input data. This demonstrates the adaptability and versatility of our AI-powered technology.
