Artificial Intelligence

Bell.One™ Intelligent Video Analytics Service allows to track large amounts of video data and offers the most effective and accurate response to potential threats. Video analytics involves the computerised processing and automatic analysis of video streams – whether live or recorded – to derive useful information about the content.

Bell.One™ provides a comprehensive and robust portfolio of data mining services that can help companies gather critical information from reliable sources.

Predictive analytics brings together advanced analytics for the prediction of data or events in the future.

Business performance management is a set of performance management and analytic processes that enables the management of an organization's performance.

Cognitive Systems is an intelligent service that allows users to independently and quickly identify the patterns and meaning of data.

Machine Learning solutions give enterprises automate analysis that has traditionally been done by humans, to learn from business-related interactions and deliver evidence based responses.

Bell.One™ offers clients neural network development as a solution to different kinds of problems.



  • Supporting diagnosis in areas such as detecting small variations from the baseline in patients’ health data or comparison with similar patients.
  • Early identification of potential pandemics and tracking incidence of the disease to help prevent and contain its spread.
  • Imaging diagnostics (radiology, pathology)


  • Autonomous fleets for ride sharing
  • Semi-autonomous features such as driver assist
  • Engine monitoring and predictive, autonomous maintenance

Financial Services

  • Personalized financial planning
  • Fraud detection and anti-money laundering
  • Process automation – not just back office functions, but customer facing operations as well


  • Personalized design and production
  • Anticipating customer demand – for example, retailers are beginning to use deep learning to predict customers’ orders in advance
  • Inventory and delivery management


  • Media archiving and search – bringing together diffuse content for recommendation
  • Customized content creation (marketing, film, music, etc.)
  • Personalized marketing and advertising


  • Enhanced monitoring and auto-correction of manufacturing processes
  • Supply chain and production optimization
  • On-demand production


  • Smart metering – real-time information on energy usage, helping to reduce bills
  • More efficient grid operation and storage
  • Predictive infrastructure maintenance


  • Autonomous trucking and delivery
  • Traffic control and reduced congestion
  • Enhanced security

Application Use Cases


Develop a predictive model based on large data sets. Identify the window of opportunity. Establish a system of regular customer evaluation. Notify churn management and retention teams within the window of an opportunity to run segment-specific churn prevention campaigns and reduce voluntary churn.
  • Decreased churn rate
  • Decreased customer service load
  • Actionable metrics


Identify customers that are going to spend the most money, in the most consistent way and over the longest period. Model the purchasing behavior of customers in order to predict their future actions and estimate their lifetime value.
  • Better than historical data prediction for new and spontaneous buyers
  • Flexible framework for different business needs
  • Dynamic micro-segmentation


By analyzing data related to lifecycle maintenance of technical equipment, our system can predict both timelines for probable maintenance events and upcoming capital expenditure requirements to streamline maintenance costs and avoid critical downtime.
  • Predict where, when, and why asset failures are likely to occur
  • Optimize spare parts inventory to reduce inventory costs associated with stockouts and overstocks
  • Inform planning and budgeting teams of upcoming issues before costly event failures occur