Take the human guess work out of the sales forecasting process by using deep learning to predict sales forecasts with increased accuracy
Understand propensity to buy - how likely a customer is to purchase a product - to help optimise marketing communications and distribution
Suggest personalised pricing to customers in sectors with complex pricing models such as insurance. Predict prices for assets such as real estate
Conduct real-time sentiment analysis to gain insight during customer service interactions e.g. determine when to switch from an automated chatbot to a human operator
Predict when incoming calls are likely to go through peaks and troughs. Combine this with an employee absenteeism prediction to optimise resource scheduling
We take a dataset, such as historical sales and market data, and organise it in a way that can be used for training an AI model.
We plug your data into an AI to train it and begin building a model. The model is customised to your data and unique to your business.
Here we further experiment with the model to improve it by continuing further training if required.
We launch the model and, depending on the requirements, build a front-end for users or integrate into existing applications.
Get predictions from you AI model directly into your Excel spreadsheet
Get predictions from you AI model directly into your Google Sheet
Import your data from your data warehouse such as Microsoft Azure Synapse and train AI models with it
Import your data from Google BigQuery and train AI models with it
Microsoft Power Apps
Deploy and visualise your AI models in Microsoft Power Apps or Dynamics
Connect to many of the apps you use in your business every day