🔧 Favorite Tools at Cardinal Geosciences: Power, Flexibility & Openness

At Cardinal Geosciences, we use a blend of open-source tools and proprietary platforms, always guided by what best fits the technical and operational needs of a project. Here's a look at the core technologies we use to build fast, reliable, and transparent geoscience workflows.

🧠 Leapfrog Geo – by Seequent

Leapfrog Geo is our go-to for 3D geological modeling. It’s dynamic, intuitive, and perfectly suited for complex geological interpretations that evolve with new data. Proprietary & Closed Source

🐍 RMSP – by GeologicAI

RMSP is a Python-based toolkit for geostatistical modeling and resource estimation. Developed by GeologicAI, it lets us simulate uncertainty, validate resource models, and bring risk-aware thinking into early-stage planning. Proprietary & Closed Source

📐 Isatis.neo & Isatis.py – by Geovariances

Isatis.neo is a powerful desktop solution for advanced geostatistics, while Isatis.py extends its capabilities into Python workflows. We use both for tasks like variography, kriging, and simulation, especially when high statistical rigor is needed in resource estimation. Proprietary & Closed Source

🗺️ QGIS – Open Source Geospatial Foundation (OSGeo)

QGIS is our everyday geospatial platform. It excels in satellite image interpretation, polygon digitization, and integration with spatial databases like PostGIS. We also develop custom plugins with interactive 2D/3D tools, ideal for mapping, drillhole inspection, and model validation. Open Source

📊 Power BI – by Microsoft

We use Power BI to communicate mining production data and performance indicators with management teams. It’s ideal for building operational dashboards that are dynamic, shareable, and decision-ready. Proprietary & Closed Source

🌐 Streamlit & Flask – Both Open Source

We rely on these Python frameworks to rapidly develop internal web apps for automating and standardizing mining workflows — from drillhole databases to geologic model validators and QA/QC tools. Fast to build, easy to deploy, and tailored to each project. Open Source

🐘 SQL (PostgreSQL, SQL Server, others)

Structured databases are at the heart of our data management approach. Whether it’s PostgreSQL with PostGIS or enterprise SQL environments, we adapt easily to manage, link, and query geoscientific datasets.

🐍 Python & Scientific Libraries

Python is the core of our analytics stack. We use libraries like:NumPy, Pandas, GeoPandas, SciPy, pyproj, shapely, rasterio, pyvista, pyarrow (Parquet), matplotlib, seaborn — to support modeling, geostatistics, spatial analysis, and visualization. Open Source

🤝 Built to Fit

We love open tools for their flexibility and transparency — but we’re equally fluent in commercial software when needed. Our goal is to work seamlessly within your stack, no matter what it looks like.

🧭 Our Approach

Use tools that are powerful, transparent, and purpose-built — to solve real-world mining and geoscience challenges.

🚀 Want to modernize your geoscience workflows? Let’s talk.

👇 Which tools are essential in your mining or geo stack?

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