Announcing the Geora climate and nature intelligence engine

Cadel Watson

Cadel Watson

Announcing the Geora climate and nature intelligence (CNI) engine

The Geora climate and nature intelligence engine powers verified, auditable proof of impact for new and existing sustainability models.

The engine allows businesses to automatically convert spreadsheets into sustainability models which back verifiable value chain incentives like insets and premiums. The models can be shared across the value chain to collect data from all participants and provide an aggregated view of nature and climate impacts.

Models powered by Geora are auditable, observable, and robust. Using Geora's asset standard system, participants can provide their sustainability data using their own data formats, terminology, uncertainties, and units; the data is then standardized and fed into the models to produce proof of impact!

The CNI Engine launches with support for Dairy Australia's Carbon Calculator and the Australian Wine Research Institute's Carbon Calculator.

Here are the top benefits of the CNI Engine:

Reduced errors

As sustainability disclosure mandates come into force, climate and nature data must be robust enough to withstand intense scrutiny.

Traditionally, climate and nature models have been consigned to spreadsheets or bespoke programs - the problem is - 90% of Excel spreadsheets contain errors, many of which have significant economic impacts. These models are brittle and are hard to understand, update, and verify.

By uploading a spreadsheet model to Geora, the climate and nature intelligence engine automatically produces a programmatic model which can detect and flag errors in the reference spreadsheet, and visualise the model in a nicer and more user friendly interface.

Share the burden of data collection

Agribusinesses are frequently required to report on their scope 3 value-chain emissions, but collecting this data is burdensome. Often, companies rely on emailed spreadsheets or forms with a frustratingly low response rate which leaves much of the true value-chain impact unknown, or based on fuzzy estimates.

Once a model is uploaded to Geora, agribusinesses can share data collection instantly across their value-chain, where each participant can contribute their information through an easy-to-use web interface, with guided help and explanations as they progress through data entry stages.

They can contribute incrementally, too, filling in information as it becomes available!

Supercharged spreadsheets

By converting an existing model into the intelligence engine, Geora supercharges the spreadsheet with additional features. All input data can now contain uncertainty and confidence levels, improving estimation, predictive value, and satisfying the IFRS S1 standard (which mandates disclosing uncertainty in reported numbers). In addition, value-chain participants can enter data using the physical units and terminology most familiar to them, with Geora’s asset standards converting them to the correct form for the model.

Making sustainability data more impactful

Data in a spreadsheet is static, and often devoid of context. To be useful and impactful, sustainability data must meet a number of criteria (see this post). Models in the intelligence engine are:

  • Verifiable, with a full audit log of data and model changes,
  • Timely, with real-time integrations with on-farm and production systems
  • Understandable, with rich explainers and descriptions
  • Comparable, both across reporting periods or seasons, and across value-chain participants

If you would like to learn more about the Climate and Nature Intelligence Engine or have a use case you’re keen to explore with us, drop us a live chat message - we’d love to hear from you!

Cadel Watson

Cadel is the CTO and co-founder of Geora