The initiative aimed to enable the identification of new potential areas for exploration of critical minerals like REE, Ni-PGE, and copper, as well as other commodities like diamond, iron, manganese, and gold within a pre-defined 39,000 sq. km area in the states of Karnataka and Andhra Pradesh, India. In alignment with these objectives, IndiaAI partnered with the Geological Survey of India (GSI) under the Ministry of Mines. The aim was to use geoscience data like geology, geophysics, geochemistry, remote sensing, borehole data, etc, to identify new target areas for mineral exploration, particularly concealed and deep-seated ore bodies.

To further these ambitions, IndiaAI and GSI launched the IndiaAI Hackathon on Mineral Targeting 2025. The initiative aimed to enable the identification of new potential areas for exploration of critical minerals like REE, Ni-PGE, and copper, as well as other commodities like diamond, iron, manganese, and gold within a pre-defined 39,000 sq. km area in the states of Karnataka and Andhra Pradesh, India. It lays emphasis on locating concealed & deep-seated mineralised bodies with depth modelling and developing AI/ ML algorithms for data cleaning, integration, modeling, and validation. Further, it aims to facilitate the generation of mineral predictive maps showing exploration targets visualised through maps, sections, etc.  

Participants had the opportunity to design and implement sophisticated AI models that can significantly enhance the effectiveness of critical mineral exploration. This hackathon was not just a competition; it was a platform for collaboration, learning, and innovation in one of the most critical areas of technology today.

Key Information

Theme

• Identifying of new potential areas for exploration of critical minerals like REE, Ni-PGE, and copper, as well as other commodities like diamond, iron, manganese, and gold within a pre-defined 39,000 sq. km area in the states of Karnataka and Andhra Pradesh, India.
• Locating concealed & deep-seated mineralised bodies with depth modelling.
• Developing AI/ ML algorithms for data cleaning, integration, modeling, and validation.
• Generating of mineral predictive maps showing exploration targets visualised through maps, sections, etc. 

Major Milestones

• Stage 1- Registration and Submission of Solutions till 13th June 2025.
• Stage 2- Evaluation Process and Presentations by shortlisted teams.
• Stage 3- Winner Announcement: Click here to see the winners list

This collaborative initiative of IndiaAI in partnership with the Geological Survey of India (GSI), represents a pioneering step toward harnessing the potential of Artificial Intelligence (AI) and Machine Learning (ML) for mineral prognostication. By integrating global best practices in data interpretation, modelling, and multi-parametric geoscience analysis, the partnership underscores India’s commitment to advancing exploration technologies. It is thus concluded that such cross-domain collaborations will pave the way for more informed, efficient, and sustainable mineral resource development across India.