Now in beta testing (Version 0.2).

Rural Automation Valuation Model

The DAS Rural Automated Valuation Model combines unique proprietary data and digital agriculture expertise with advanced predictive models to instantly value any rural or farming property in Australia.


When Digital Agriculture Services (DAS) was selected as part of the inaugural Westpac FUELD cohort, we began developing and testing a data-driven idea – could we deliver a solution that algorithmically determines rural property values?

While Automated Valuation Engines are an increasingly common tool for residential and commercial values, the complexity of predicting rural values in Australia – a nation characterized by diverse terrain, disparate data and complex land dynamics – has prevented the development of an automated farmland valuation model.

No longer. Digital Agriculture Services believes its Rural Automated Valuation Model will transform rural property and real estate assessment.

The DAS Rural AVM is a statistical, machine-learning model that algorithmically determines values so it isn’t perfect but is continuously improving with public and user-submitted data.

The DAS Rural AVM valuation is an automatically calculated, independent estimate of market value. It is not an appraisal or formal valuation, and is most often used as an unbiased starting point.

The DAS Rural AVM uses a machine learning approach, but integrates agriculture-specific attributes like soil, rainfall or productivity with multiple other variables and characteristics.

Gathers a pool of data on any single rural property in Australia, including farming properties not currently on the market, and is presented within a google satellite map-driven interface.

The DAS Rural AVM currently delivers 92% of all estimated valuations within 20% (+/-) of the sales price and is continuously improving and updating.

The DAS Rural AVM is believed to be the first, dedicated rural-specific AVM in Asia Pacific – and the only AVM to have been developed, referenced and validated by Data 61 and CSIRO.

Predictive Model

Evidence-Based Guidance

Rural-Specific Attributes

Map Based Interface

Greater Accuracy

Rural Property Specific

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