SmartIntelligence™ customers make proactive decisions using artificial intelligence

The powerful rules engine technology means that alerts can be triggered around specific events, pushing business critical information to business managers. SmartIntelligence™ is much more than just business information, it pinpoints business and/or management opportunities.

“SmartIntelligence has enabled our customers to truly leverage the power of their data and deliver insight. For one of our clients, enriching and visualizing their data into actionable insight for their sales team resulted in return on their investment within the first few months of usage” Matthew Attwell, Risk and Client Services Director at ai.

ai’s predictive neural modelling/machine-learning tools also provide “a-state-of-the-art” forecasting capability. These predictive models exploit patterns found in historical and transactional data to identify risks and opportunities, and give the capability to carry out key value elasticity modelling across a business.

“ai has tackled an incredibly complex data landscape to produce operational insight on an ongoing basis, via a custom-built tool that is integrated into users daily work. We’ve been impressed by their agile approach to deploy, their speed of turnaround and their consistent focus on ensuring success.” Andrew Johnson, Integrated Solutions Manager, Shell

Seeing the wood for the trees is imperative, therefore ai has developed the following framework:

  1. 1. Data Centralization – To help aggregate the data sources. It is important to note that the fraud system, typically, is one of the best sources of data in an organization and can be easily augmented from other corporate data sources.
  2. 2. Reactive Play Back – To expose critical information and KPIs required by your organization e.g. underperforming sales team.
  3. 3. Proactive – To proactively alert management teams to opportunities. By using ai’s highly sophisticated rules engine technologies, specific rules can be set up to trigger specific events – both good and bad.
  4. 4. Predictive – To enrich the data using other external sources such as Social Media, demographic information and telematics. By supplementing current data sources with these pools of information, ai’s neural technology can be deployed to provide business forecasts across the business.
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