ALEX’s extraordinary flexibility allows it to host multiple solutions across multiple industries. ALEX thrives in a dynamic environment with industry-scale data streamed in real time. Solutions include data input, models, and actions that correspond with achieving key user objectives.


ALEX acts as an external component for IOT platforms that want to enhance their current platform to include AI. ALEX will allow IOT platforms to automatically produce predictive models based on the data that is being streamed through the IOT platform. As part of the AI component, ALEX is equipped with a high-performance work-flow engine allowing the IOT platform to automatically react to the machine learning predictions. ALEX as an AI component for IoT platforms is scalable with transactions processing lower than 100 milliseconds, carrier-grade 24/7 up-time, and provides multiple device and protocol connections. Currently, the platform is in a communication service providers network supporting over 100 million of its subscribers.



Telecommunications operators and enterprises that view Net Promoter Score as a major KPI metric for their business can use ALEX to predict NPS scores for the telco/enterprise’s customers. Data such as network and operational events are streamed to ALEX the NPS models hosted in ALEX determine the root causes for each of the subscribers that could be classified as detractors. The root causes are used as actions to the telco/enterprise to identify how to improve the quality of the service the business is providing. Once changes are made in the network or operations, the models are automatically tweaked by ALEX to ensure continuous improvement. In addition to providing a continuous customer experience understanding, the operator can also use the findings to determine which subscribers should be targeted with promotional offers to prevent Churn.



ALEX monitors data in real-time coming from wearable technologies such as CGM (Continuous Glucose Monitoring), smart watches, fitness trackers etc to produce Blood Glucose predictions in the future for diabetics. These BG models make predictions for both Type 1 and Type 2 diabetics predicting blood sugar levels in hourly intervals. ALEX creates a model per each individual taking into account that persons habits.



Small to medium enterprises who do not have the in-house data science expertise or the budget to outsource this work can turn to ALEX.  By simply connecting data to ALEX in the cloud, enterprises can immediately start to put predictive models into action to enhance their business.  ALEX has an easy to use API which is readily available and an intuitive Graphical User Interface for the business users to tell ALEX what to predict and how to act.  ALEX in the Cloud comes with an affordable SaaS pricing model and a small cloud footprint making the business case to hire ALEX justifiable.



DANATEQ uses its real-time AI models with streaming data to predict battery power losses that cause mobile radio stations to be disabled. The predictions are made in order to give ample time for the network engineer to reach the station before it fails. Other preventive maintenance predictions can be determined by generating additional models for the different components that make up the network and IT infrastructure.



Using ALEX for vending retail management, predictive models and actions are automatically generated to determine when the machines need to be refilled and what items need to be delivered to the machine for stocking. In addition, the maintenance and re-stocking routes are optimized in real-time for the operator. Preventive maintenance predictions are determined by ALEX so that the machines will stay in service without failures.

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