Fontaine dbMax Solutions, Inc
Machine Learning, Software, and Data Solutions for Hydrogeologic Decision-Making
A quote from our founder
We help your engineering teams solve their most difficult hydrogeologic data and modeling challenges! - Russ
Who We Are
Fontaine dbMax Solutions, Inc. is a Colorado-based consulting firm specializing in machine learning, software, and data solutions for hydrogeology and environmental engineering. We work with engineering teams that manage complex scientific datasets and need reliable, defensible insights to support real-world decisions.
Our work sits at the intersection of domain expertise and modern technology. We understand hydrogeologic data, environmental monitoring programs, and regulatory-driven analysis — and we build practical tools, workflows, and models that turn data into actionable intelligence.
Whether you are evaluating groundwater risk, integrating disparate datasets, or exploring machine learning to enhance traditional modeling approaches, we help you move from raw data to informed decision-making with confidence.
Why Should You Consider Us?
Hydrogeologic and environmental data are complex, heterogeneous, and often difficult to integrate, analyze, and interpret. Traditional workflows can be time-consuming, brittle, and hard to scale — while off-the-shelf analytics tools rarely reflect the realities of field data, uncertainty, and regulatory context.
At Fontaine dbMax Solutions, Inc., we bring deep experience working with hydrogeologic, geologic, and environmental datasets alongside modern machine learning and software engineering practices. We understand both the science behind the data and the technical challenges of managing, modeling, and visualizing it.
Our approach helps engineering teams streamline data workflows, improve analytical rigor, and explore advanced methods — such as machine learning — in a transparent and defensible way. The result is better insight, reduced friction in data handling, and stronger technical support for high-stakes decisions.
Services We Offer
Machine Learning for Hydrogeologic Risk & Insight
We apply machine-learning methods to hydrogeologic and environmental datasets to identify patterns, quantify risk, and support decision-making.
Our work emphasizes transparency and interpretability, using techniques such as feature attribution to ensure results are scientifically defensible and appropriate for regulatory or engineering contexts.
Typical applications include groundwater risk assessment, contaminant occurrence modeling, spatial prediction, and exploratory analysis to complement traditional modeling approaches.
Data Management & Workflow Foundations
Effective machine learning and analytics depend on well-structured, well-understood data. We help engineering teams organize, integrate, and quality-check complex environmental datasets to create reliable analytical foundations.
This includes database design, workflow automation, data quality review, and reproducible data pipelines that reduce friction and improve long-term maintainability.
Custom Software & Decision-Support Tools
We design and develop custom software tools that make complex data and analytical results accessible to technical teams and stakeholders.
Solutions may include interactive dashboards, modeling workbenches, and internal tools that integrate data management, analysis, and visualization into a single workflow — tailored to your organization’s needs.
MasterAppML™ and Groundwater Risk Case Study
MasterAppML™ is our internal machine-learning workbench designed to support reproducible, interpretable analysis of environmental and hydrogeologic data. It integrates data exploration, cleaning, model setup, execution, and review into a single workflow.
To see a demonstration of our Colorado Groundwater Nitrate Risk Case Study or learn more about MasterAppML™, please contact us.