Our Story
From humble beginnings.
-
2019-2020
From Ideas to Inception
Artificial Intelligence algorithms have advanced in other areas but applications in the minerals industry were still scarce — so it was uncertain whether AI was mature enough to identify complex minerals in process slurries in real-time. There is a market gap for real-time mineralogy so the right AI algorithms combined with the latest imaging hardware would open up mineralogy based process control. We executed extensive testing to select the appropriate microscopy configuration, sampling procedure, and AI algorithm.
-
2021-2022
Proof-of-Concept Study
We verified our methodology of detecting minerals using flotation samples from a poly-metallic sulphide deposit in NSW, Australia. We compared the grades calculated from the identified minerals against assay tests of the same samples from a laboratory. Our methodology was able to predict Cu, Pb, Zn, and S grades with high accuracy - confirming that our methodology detected the mineralogy correctly. The results were peer-reviewed and published in a journal.
-
2023
Prototyping
With the concept proven, we focused our efforts to packaging the methodology into robust and portable forms for commercial use cases. With feedback from sites and domain experts, we planned for separate devices for use in the laboratory in batch mode and in the concentrator in continuous mode.
-
2024
Commercial Ecosystem
As interest in the technology developed, we entered an ecosystem with Orica who provided some development funding. Core Resources, a commercial laboratory also contributed spaces to conduct further testwork and prototyping.
