Each vertical in the marketplace involves unique subject matter and processes, but each has a common need for advanced analytical insights and tools to succeed in an ever-changing globalized economy. 

Datos Technologies serves this need across verticals and provides customized solutions catered to each vertical.  

Data Science Around the Globe

Know the aftermarket business before it happens by leveraging advanced predictive analytical solutions.

  • Predict demand for inventory deployment.
  • Anticipate and plan for warranty and recall issues.
  • Optimize pricing and inventory for customer acquisition and retention strategies.
  • Improve service scheduling with IoT data from sensors in components and subsystems.
  • Improve product quality by informing upstream processes in manufacturing quality, supplier quality, and product development quality.
  • Increase the lifetime value (total revenue) from servicing the installed base.

Increase the wealth of an organization by managing and improving the health of its employees.

  • Scheduling workforce by using algorithms to predict future admission trends.
  • Predictive analytics to reduce re-admission rates and in the areas of behavior, risk and fraud.
  • Cloud-based system using big data, analytics and machine learning to create prescriptive decision making for better patient outcomes.
  • Platform for data aggregation, distribution and analytics for outcome based healthcare.
  • Big data and advanced analytics for financial analysis, cost management, pharmacy benefit management, and clinical improvements.
  • Improve operational efficiency and patience care through IoT-enabled solutions.

From enterprise level to the line level incorporate data science to optimize production and generate the highest value.

  • Optimize production planning and scheduling.
  • Machine learning algorithms to optimize capacity utilization.
  • Automate performance driver and bottleneck identification to predictively mitigate process fluctuation.
  • Optimize the first-pass yield by tracking in real-time variances that affect quality.
  • Automated dashboards for tracking and reporting including IoT information.
  • Predictively monitor asset failures to minimize line down-time.

Build market share and personalize customer experience through innovative Big Data strategies.  

  • Artificial Intelligence (AI) to sense and predict demand and prescribe inventory deployment strategies.
  • Use unstructured data to “listen” to your customer and AI to design marketing campaigns to attract and retain them.
  • Analytics to improve layouts, promotional displays and product placements. 
  • Machine learning algorithms to create dynamic restocking and assortment strategies.
  • Advanced analytics to measure shoppers’ response to price, promotion and markdown strategies.
  • Big Data analytics to maximize the lifetime value of the customer.


Drive your organization’s supply chain in top gear with data-driven solutions.

  • Predictive analytics to forecast inventory and optimize labor requirements.
  • Blockchain solution for securely and transparently tracking all types of transactions across the supply chain.
  • Big data analytics for optimizing capacity utilization, reducing risk, improving customer experience and creating new business models.
  • IoT cloud-based collaborative platform for end-to-end supply chain tracking and optimization in real-time.
  • Last mile route optimization using GPS-enabled Big Data telematics.
  • Optimize warehouse slotting to improve space and increase picking efficiencies.


Radically transform wholesale distribution to create new sources of revenue and increase margins to foster profitable growth.

  • Artificial Intelligence (AI) to sense and predict demand and prescribe inventory deployment strategies.
  • Advanced analytics to determine the net profitability of a sale including returns, discounts, promotions, and buy-backs.
  • Predictive analytics to target customers with products and services, and reduce risk.
  • Predictive analytics for New Product Introduction (NPI) based on historical NPI launches and other product profiles.
  • Apply predictive analytics to CRM and accounts receivable (AR) to monitor individual and group of customers for credit defaults.
  • Optimize labor scheduling in the warehouse based on number of orders and order profiles.