About
Stratum AI is a deep-tech AI platform purpose-built for the mining industry, enabling companies to unlock hidden value from their mineral resources. At its core is SAIGE (Stratum AI Geostatistical Engine), a proprietary technology that learns from high-density multivariate geostatistical data and applies those learnings to model complex geological environments with lower data density. The platform supports critical mining workflows including resource estimation, grade control, geometallurgical modeling, and geotechnical analysis. It is designed to enhance decision-making during production and brownfield expansion — the phases where operational decisions carry the greatest economic impact. Stratum AI has demonstrated compelling results across multiple mining projects: a 41% reduction in waste produced, a 6% increase in yield, a 58% reduction in tonnage deviation, a 20% improvement in high-grade stockpile grade, approximately 25% fewer drilling requirements, and a 10% increase in overall production. The platform also supports improved drill targeting, dynamic reconciliation, and error correction. Targeted at mining operators, geologists, and mine planners at mid-tier to major mining companies, Stratum AI bridges the gap between raw geological data and actionable mine plans. It is particularly well-suited for gold and copper operations, as evidenced by its published ASX case studies. By integrating AI into core resource modeling workflows, Stratum AI helps miners increase NPV, reduce operational risk, and optimize resource utilization.
Key Features
- SAIGE Geostatistical AI Engine: Proprietary deep-tech AI that learns from high-density multivariate geostatistical data and applies those insights to lower-density geological environments for accurate resource modeling.
- Grade Control Modeling: AI-driven grade control models that reduce tonnage deviation and increase high-grade stockpile accuracy, directly improving mined grade and yield.
- Mine Planning Optimization: Supports brownfield expansion and production decision-making by generating optimized mine plans that maximize NPV and minimize waste.
- Geometallurgical & Geotechnical Models: Builds comprehensive geological models that incorporate metallurgical and geotechnical factors for holistic mine design and risk management.
- Dynamic Reconciliation & Error Correction: Continuously reconciles geological predictions against actual production data, identifying and correcting errors to improve future model accuracy.
Use Cases
- A gold mining operator uses Stratum AI's SAIGE engine to build grade control models from existing high-density drill data, reducing waste by 41% and increasing gold yield by 6% across active mining blocks.
- A copper mine's geology team applies Stratum AI to improve resource estimation in a brownfield expansion area with sparse drilling, transferring statistical learnings from a nearby well-drilled zone to reduce required new drill holes by 25%.
- A mine planning team integrates Stratum AI models into their scheduling workflow to maximize NPV by accurately identifying and prioritizing high-grade ore zones within the mine plan.
- A mining company uses dynamic reconciliation features to compare predicted versus actual production tonnages, identifying systematic geological modeling errors and correcting them in real time to reduce tonnage deviation by 58%.
- A junior mining company preparing for an ASX listing leverages Stratum AI to produce robust geometallurgical and geotechnical models, improving investor confidence in their resource estimate and mine plan.
Pros
- Proven, Measurable Results: Published case studies for gold and copper mines show up to 41% waste reduction, 6% yield gain, and 10% production increase — concrete economic benefits.
- Works with Sparse Data: SAIGE technology enables accurate modeling in low-density drilling environments by transferring knowledge from high-density datasets, reducing the need for costly additional drilling.
- Covers the Full Mining Workflow: Addresses resource estimation, grade control, geometallurgy, and geotechnics in a single platform, reducing the need for multiple point solutions.
- Reduces Drilling Costs: AI-powered drill targeting and fewer required drill holes (approximately 25% reduction) translate into significant capital savings.
Cons
- Highly Specialized Domain: Exclusively built for the mining industry — not applicable to other sectors or general-purpose data analytics needs.
- Enterprise Pricing: As a deep-tech enterprise solution for mining companies, pricing is likely significant and may be out of reach for smaller junior mining operations.
- Limited Public Documentation: Technical documentation and pricing details are not publicly available, requiring direct engagement with the Stratum AI team to evaluate the platform.
Frequently Asked Questions
What is SAIGE technology?
SAIGE (Stratum AI Geostatistical Engine) is Stratum AI's proprietary deep-tech AI engine that learns multivariate geostatistical patterns from high-density data and applies them to model geological environments where data density is lower, enabling more accurate resource and grade control models.
What types of mines does Stratum AI support?
Stratum AI has published case studies for gold and copper mining operations, but its AI platform is applicable to various mineral commodities where resource modeling, grade control, and mine planning are critical.
How does Stratum AI reduce waste in mining?
By producing more accurate grade control models, Stratum AI enables mine planners to precisely identify ore versus waste material, reducing the amount of waste rock processed and increasing the average mined grade — demonstrated at up to 41% waste reduction in project results.
At what stage of the mining lifecycle is Stratum AI most useful?
Stratum AI is specifically designed to deliver impact during production and brownfield expansion phases, where operational decisions have the greatest economic consequences. It can also improve drill targeting during exploration.
How do I get started with Stratum AI?
Stratum AI is an enterprise solution — interested mining companies should contact the team directly via the website to discuss project needs, available data, and commercial arrangements.
