Fontaine dbMax Solutions, Inc
Our Mission
Fontaine dbMax Solutions helps engineering teams make defensible decisions from complex hydrogeologic and environmental data. We combine domain expertise, modern software engineering, and machine-learning methods to deliver transparent, auditable, and decision-ready solutions.
Environmental datasets are increasingly large, heterogeneous, and difficult to interpret. Decisions based on this data often carry regulatory, financial, and public-safety consequences. Our goal is to reduce uncertainty and friction in your workflow—so your team can move from raw data to reliable insight with confidence.
Our Approach
Domain-first Modeling
We start with hydrogeologic understanding—not algorithms. Models and analyses are built to respect physical processes, data limitations, and the realities of field data and regulatory context.
Interpretability over Black Boxes
We emphasize methods that explain why predictions are made—using techniques such as feature attribution, sensitivity analysis, and spatial diagnostics—so results are understandable and defensible.
Engineering-grade Workflows
We build reproducible, auditable pipelines that integrate data management, modeling, and visualization—designed for internal review, client communication, and long-term maintainability.
Leadership & Expertise
Fontaine dbMax Solutions was founded by Russ Fontaine, P.E., a licensed professional engineer with decades of experience spanning hydrogeology, environmental engineering, and software development.
Russ has led technical teams across the energy, mining, and environmental sectors, serving in roles that combine engineering judgment, data analysis, and product development. This background shapes how we approach every engagement: with an emphasis on technical defensibility, clarity, and practical implementation.
Credentials & Capabilities
- Licensed Professional Engineer (Colorado)
- Hydrogeologic & environmental data analysis and modeling
- Machine learning for risk assessment and spatial prediction
- Custom software development (Blazor / .NET / Python)
- Cloud data platforms (Azure App Services, Azure SQL)
Education
- Petroleum Engineering — Texas A&M University
- Geological Engineering — Colorado School of Mines
Whether you are modernizing legacy workflows, evaluating groundwater risk, or exploring how machine learning can support engineering judgment, we partner with your team to turn complex data into clear, defensible insight.