1024 683 Rob Wood

Exploration is fundamentally speculative. It has always been a high cost/high risk business model in terms of return on investment.  Compounding explorations relatively high risks are two underlying challenges:

  1. The geological information that resource companies currently have remains largely locked in static unintegrated formats (paper and pdf’s) with labour intensive processes to digitize and place into coherent data structures.  
  2. Geologists and resource companies are typically drowning in a sea of multi-faceted data (maps, tables, reports) attempting to correlate, extrapolate and make predictive decisions by combing through a narrow band of the enormous amounts of data they actually hold.

These challenges seriously limit the degree and quality of analysis being performed and leads to consequential decision-making barriers: where to explore, how much to invest, which companies to acquire and the valuation on existing and potential assets.

Historically, exploration has been at the front end of the mining life cycle. Today, the frontiers of exploration should begin with a deeper analysis of the data.  This deeper examination requires an integration of emerging capabilities: data aggregation, machine learning, predictive analytics, and graphic visualization.

This new frontier requires companies that can:

  • aggregate, correlate, synthesize and then apply complex analytics across vast amounts of data; and then,
  • provide graphically sophisticated representations of the data in an manner accessible to professionals by augmenting rather than replacing existing decision-assisting tools.

The challenge is that even the most sophisticated systems on the market today are generic data aggregation, prediction and visualization software tools. They are simply agnostic tools for all industries and sectors.

KOAN Analytics’  Resource Aggregation, Analytics, & Visualization (RAAV) is the first and only complete analytics solution designed specifically for the resource sector.  We have incorporated leading edge tools and have built machine learning logic specifically for resource exploration.  The consequence: our RAAV system isn’t trying to apply data aggregation or predictive analytics across all sectors and industries.  RAAV is vertically deep and focused exclusively on resource exploration.

RAAV has been developed in collaboration with the experts who will use it. We understand that businesses don’t stop when new capabilities are introduced, so our platform has been designed to seamlessly integrate into existing systems and workflows such as Arc-GIS.

Importantly, we do not aim to take the human out of the equation – we are providing new equations and tools to assist geology experts and business executives discover as yet unseen insights that substantially improve their decision-making.

Individually, each component of RAAV is a powerful improvement in exploration analytics; combined, they are a force multiplier in reducing exploration costs, enabling better investment and acquisition decisions and unlocking the true potential of company assets.

Only Koan Analytics has the combined capabilities across this new pre-exploration frontier.  

Come discover the New Wild West.