Why MaxMine

MaxMine was founded in 2015 – building on the team’s 15-year legacy in business
improvement and data-intensive process efficiency, improvement in mining, mineral processing,
oil and gas and large-scale manufacturing.

We are a group of expert problem solvers, passionate about solving real-world challenges with innovative and tangible solutions that stick. We are agile, flexible and value driven. We are continually verifying and validating our view of your world, asking ourselves the following:

Our Mission

To improve operational efficiency, profitability, safety and sustainability significantly and permanently in large-scale asset-intensive industries across the globe.

Our Vision

To build the most compelling operational technology platform in the industrial world. To take this well-developed, proven technology and apply it to key asset-intensive sectors globally.

Our Technology

We have built a robust, full-stack IoT-AI-BI platform that is improving operations globally.

We work with a range of technologies across the full spectrum of dev-ops (software application development and IT operations) and data-science.

MaxMine is not a recent entrant to the fields of business
improvement, machine learning or data intensive analysis.

Our leaders have been doing vehicle communications and data-intensive analysis since 1996, machine
learning since 2001, and our founders have been drawn from senior roles in top-tier operational
improvement firms and mining operations.

What We Stand For

MaxMine has created unique, outcome-driven solutions based on what we as a collective group test and develop.
Our success springs from a strong company culture of shared values:

An open and honest approach to communication within our team, externally

and with all our key stakeholders

An industry that always challenges the norm and accepted systems, to create a future that delivers a strong bottom line for our clients and, therefore, for us
Continually improving our system and the way we do business to enable flexibility and
fit-for-purpose solutions
Focusing only on what matters
and fixing that first
Implementing improvements that last so
that we only fix something once