Predictions as a Service

Predictions as a Service is a powerful decision-making platform. It has been designed by our team of BI experts to provide valuable predictive analytics insights for use within human resources, retail, HE and customer services.

The service enables any organisation to leap into the world of predictive analytics without necessarily having to recruit Data Scientists or make sizeable hardware and software investments.

Regardless of organisation size, this cloud-hosted solution will improve your competitive advantage by providing real-time predictions. These are combined with the analytical capability required to highlight complex patterns of behaviour in your data.

Predictive Analytics: Use Past Data to Predict Your Future

The rate at which organisations gather and store data is rapidly increasing - and the potential value of that data is huge. Through Predictions As A Service, we help you to unlock that hidden power.

No longer will your historical data consume vast amounts of storage without any real purpose. It can now be used to make predictions about the future!


Vitally, our predictive analytics service is incredibly secure. Hosted on the Oracle Cloud, it works off anonymous data – which means that there is no requirement to upload data that could be used to identify customers or other individuals.

  • Cloud hosted
  • Automated/instant predictions
  • 24x7 Availability
  • 100% Secure
  • Enabled for Mobile BI
  • Monthly all-inclusive service fee

We would be delighted to give you a demonstration of Predictions as a Service and discuss options for performing a trial run.  Please contact us.

Real-Life Examples

Listed below are some real-examples where Predictions As A Service could add real business value to your organisation. If there are other ideas you have relevant to your industry that aren’t listed here, please get in touch to speak with our Predictive Analytics team.

Predictive Analytics for Human Resources

  • Predicting which employees are likely to leave in the next year
  • Predicting which employees are likely to be high performers
  • If we give an employee a promotion or pay rise, will they be less likely to leave?

Predictive Analytics for Retail

  • Predicting stores that will have out-of-stock products
  • Predicting sales based on the weather forecast
  • Which customers are likely to be interested in our marketing campaign?
  • What other products is the customer most likely to be interested in?

Predictive Analytics for Higher Education

  • Predicting which students are most likely to leave their course early
  • Predicting which students are most likely to accept an offer

Predictive Analytics for Customer Services

  • What is the likelihood that this customer will churn?
  • Which offer is the customer most likely to accept?