July 4, published October 1

Our first data in support of our FactSet partnership is being delivered with a new data architecture: all inputs, including relevant machine learning models, are carefully stored, ensuring we can reconstruct data generated by Emmi at specific dates, in the future.

Reproducibility is important for completing tasks like re-baselining of emissions for a target, based on improved methodologies, or just for the purposes of audit or customer data-loss. But before any systems or processes can reproduce data, they requires a meticulous set of records and data as inputs, which is now in place as part of our core technical architecture.

Benefits:

• Assurance of reproduction of emissions estimation and risk data delivered after this date