Overview
Stratum AI builds machine learning software for mining companies to predict the distribution and quality of minerals before deciding what to extract and process. Its SAIGE platform turns geological logs, drill results and operating data into three-dimensional models of deposits, with applications in resource estimation, ore classification and processing. Mining teams upload data through a web dashboard, inspect model results and use the outputs to plan work at a mine. The company sells its proprietary modelling technology to mine operators, with technical specialists adapting models to each site's geology and operating needs. Stratum AI is headquartered in Toronto, Canada.
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Simplify's take
What believers are saying
- Deployment spans borders: Stratum reports experience across 18 mines in 10 countries.
- Remote engineering is explicit: Stratum's full-time Machine Learning Ops Engineer opening is based in Canada.
- Design pay is published: Stratum's remote, full-time Canada 3D Product Interface Designer contract advertises CAD 45-80 hourly.
What critics are saying
- Data requirements narrow Stratum's market: its SAIGE software excludes greenfield exploration and requires sufficient geological control.
- Stratum's remote-first Forward Deployed Machine Learning Engineer role is full-time, prefers Canada and requires at least two annual mine visits.
- Stratum's remote-first, full-time Full Stack Engineer opening prefers Canada and expects occasional odd hours, including potential weekend calls.
What makes Stratum AI unique
- Established workflows remain usable: Stratum's SAIGE outputs integrate with conventional statistical estimation methods.
- Rock classes get separate models: Stratum's SEAM pit-wall assessment software trains a dedicated expert for each class.
- Model reasoning is visible: Stratum's SEAM heatmaps show which rock-face areas drove each prediction.
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