The startup utilizes machine learning algorithms in conjunction with a proprietary dataset to identify large copper, gold, nickel, and lithium deposits in underexplored regions of central Asia. This approach enhances the probability of discovering significant mineral resources, addressing the challenge of inefficient exploration methods in these areas.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional mineral exploration in Central Asia faces challenges due to the region's vastness and limited application of modern exploration techniques, despite its known mineral wealth. Inefficient exploration methods hinder the discovery of large copper, gold, nickel, and lithium deposits.
Solution
Pallas Resources employs machine learning algorithms and a proprietary dataset, built from digitized Soviet-era exploration data, to identify promising mineral deposit locations in Central Asia. This big data approach enhances the probability of discovering significant copper, gold, nickel, and lithium resources by integrating geophysics, geochemistry, geology, alteration, deposit, and structural data. The company ranks opportunities for Tier 1 prospectivity and scrutinizes them at a belt-scale, focusing on under-explored regions ripe for modern exploration. Pallas Resources actively consolidates district-scale positions in copper provinces and forms strategic alliances to advance exploration projects.
Target Audience
Pallas Resources primarily targets investors and joint venture partners seeking exposure to a portfolio of assets with significant discovery potential in Central Asian mineral belts.
Features
- Largest private exploration dataset covering Central Asia, including decades of digitized Soviet-era data
- Machine learning prospectivity tool combined with country-wide datasets for ground selection
- Portfolio of projects targeting copper, gold, nickel, and lithium in Kazakhstan's premier mineral belts
- Exploration partnerships with industry leaders for porphyry and sediment-hosted copper systems
- Expertise in orogenic and epithermal gold systems, sediment-hosted, and porphyry copper deposits
- In-house specialists in machine learning, spectral geology, and remote sensing
- Ability to rapidly digitize and dissect Soviet-era datasets