BEST-IN-CLASS MACHINE LEARNING
Remi Ai’s Demand Forecasting API is an AutoML deep learning api service for demand forecasting and time series analysis. It enables you to quickly and cheaply start utilising best-in-class algorithmic approaches for your supply chain forecasting.
These methods can be up to 50% more accurate than traditional time series approaches. By providing historical time-series data from a range of data streams, you can accurately predict future time series. This is useful for numerous industries including E-Commerce, Retail, Manufacturing and Wholesale Distribution.
Our Demand Forecasting APIs are built on top of a suite of machine learning and traditional time series methods. Our AutoML methods deliver the best model for every single product across your product range.
BUILT IN DATA
Our demand forecasting APIs have weather data and other data built in, meaning you can quickly and easily understand the impact these factors are having on your sales.
You simply need to provide longitude and latitude of your outlets to understand how the weather is affecting sales, this can then be used in conjunction with current forecasts to help with the short-term forecasting.
LOW VELOCITY FORECASTING
Our Demand Forecasting APIs have specifically designed models to deal with SKUs that don’t sell at a high frequency, but are still critical to forecast correctly.
Where other forecasting approaches predict ZERO sales, our low-velocity demand forecasting allow us to provide actionable insights into which of your products will sell and when.
Behind our Demand Forecasting APIs are 12 different time series methods, including deep learning, probabilistic, arima and other models to choose from.
But you don’t need to know anything about these models, instead our AutoML service handles all the training, optimisation, testing of the 12 models, so you know you’re guaranteed the best model for your specific data.
This model and its parameters are saved for each of your products, ready to deliver forecasts as new data becomes available.