Why Harmonee?


Daisee Harmonee accurately predicts sales ahead of time for each product and each store location based on a range of historical factors. To determine an accurate forecast, it combines structured data, such as sales, with external data such as weather and calendar.


Daisee Harmonee monitors inventory and opportunity costs, ensuring that shelves are always stocked with enough of the right products. This minimises loss of perishables while maximising sales and customer experience.


Daisee Harmonee also determines the best prices for each product at a given point in time, based on supply and demand. This can be used by companies to identify opportunities and administer promotions at the right time.

Case Study


Fresh Flowers Group needed better ways to forecast supply and demand. This was particularly challenging given the perishable nature of its products and the extreme volatility in demand (driven by various calendar events such as Valentine’s Day).


We fed in historical point-of-sales data and augmented it with significant calendar events (e.g. Chinese holidays). This model was tested with 3 months of hold-out data, comparing losses from overstock/understock scenarios.


The insights generated by daisee Harmonee allowed business rules to be created in order to make predictions about future stock purchases. AI prediction gave significantly better results than a traditional Excel regression method

There were peaks and troughs in our business that I did not realise were there. We had totally missed a couple of peak periods.

- PETER LYNCH, Fresh Flower Group, CEO