No. Stratum AI complements traditional geostatistical workflows. AI-generated domains and outputs can be integrated into conventional estimation methods such as kriging, following existing site standards.
Models are validated through internal consistency checks, comparison with existing site models, reconciliation against production data where available, and review by site technical teams.
SAIGE models can be updated as new drilling, grade control, or operational data becomes available, allowing the model to evolve alongside the mine.
No. Stratum AI focuses on production-mines and brownfield environments, where sufficient data density and geological control exist to support reliable modelling and operational decision-making.
No. Stratum AI’s models are designed to be interpretable and grounded in geological reasoning. We provide visibility into how different data inputs influence predictions and how spatial relationships are learned, allowing technical teams to review results at a block-by-block level.
Stratum AI uses existing site data, including geological logs, assays, and operational datasets. No additional data collection programs are required to generate models.
Models operate at block scale and are designed to respect geological continuity while capturing local variability that may be smoothed by traditional approaches.
Stratum AI works closely with site geologists and engineers to incorporate geological understanding and operational constraints into the modelling process.
SAIGE delivers the greatest value in areas such as grade control, mine planning, brownfield expansion, and reconciliation, where improved spatial understanding directly impacts economic outcomes.
Final model validation, estimation, and public reporting remain the responsibility of the site team and the Competent or Qualified Person, following NI 43-101 / JORC guidelines.
Model outputs can be exported in standard formats compatible with existing mine planning and geological software, ensuring integration with current workflows.
Yes. In addition to grade, SAIGE can model mineral and rock characteristics such as hardness, fines generation, and other parameters relevant to processing and geotechnical performance.
