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Carefully Selected. Rigorously Tested. Enterprise-Ready. Original algorithms for data scientists to read, use and share.

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Multi-variate data comprehension 

 Ai-Rover™ Explainable AI Notebook

Case Studies

AI systems tend to operate in the darkness of black boxes. Input data is transformed into decisions without much human-readable justification. The journey from data to insights requires a crucial data comprehension stage, so the direction of an AI/ML model is fully explainable. Omitting this stage may produce a result that is not actionable, causing the AI project to dead-end.

Ai-Rover™ is the full implementation of an explainable AI algorithm on a virtualized notebook, in concert with Zeblok's GPU-powered data lake, Edge connectivity and other components.  Ai-Rover™ discovers and visually explains patterns in complex datasets as well as the causal relationships underlying those patterns, supporting data analysts in the construction of trust-able decision-making AI models. Zeblok's accelerated data lake enables rapid querying of multiple disparate data sources. Ai-Rover™ enables the crucial data comprehension phase to properly target the direction of an AI project.

Say goodbye to tedious data exploration and instead gain quick access to the hidden information in your data within an easy to understand visual interface that enables users to intuitively derive subpopulations of data attributes, leading to better predictive insights.

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 Ai-Rover™ for time-series data

Time-series data forecasting & anomaly detection 

Ai-Rover™ for time series is a value framework to automate predictive model-building that creates human-readable models from historical time-series data. These models provide users with high-quality explainable forecasts and anomaly detections, creating business value in use cases across industries. 

The framework is built on a field of mathematics called information geometry, an interdisciplinary field that uses differential geometry techniques to study probability theory and statistics. It enables model building which includes business focus, aggregates, and key performance indicators (KPIs). It can help you identify the value of the predictive analytics business use cases that you want to implement. 

Typical use cases and business applications:

•    Demand/capacity prediction
•    Predictive asset management
•    Fraud/anomaly detection
•    Marketing/social analysis
•    Pricing optimization
 

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Use Cases
Case Studies

Ai Video-Analytics-as-a-Service

Near real-time Ai- Video-Analytics

A robust framework that enables development and implementation of AI-powered video analytics solutions. It accommodates video feeds in a variety of formats & resolutions, ranging from a few cameras to thousands of cameras; best in class annotation tools to generate unlimited number of datasets with precise guidelines and complex ontologies to significantly reduce labeling time and an inference engine to integrate your production output into your enterprise application from Core to Edge using RESTful API.


Offer Video-Surveillance-as-a-Service by developing bespoke AI models to a variety of clients responsible for monitoring facilities, such as schools, highways and public spaces to identify vandalism and other suspicious behavior, monitor and analyze traffic patterns, identify traffic violations to providing Quality audits for manufacturing processes in automobile industries. 

Enterprise applications include:
•    Intrusion Detection
•    Suspicious Activity
•    Traffic & Parking Management
•    Smoke & Fire Detection
•    Crowd Counting
•    Vehicle Identification
•    Non-Invasive Body Temperature Monitoring
•    Dwell Time
•    Safety gear monitoring – Hardhats, safety goggles, masks

Case Studies
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Entropy-as-a-Service

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Quantum entropy for a connected world

  • Qosmos™ is an Entropy-as-a-Service (EaaS) offering that provides quantum random numbers as a simple web-based service, delivered via container on Ai-MicroCloud™ to the network security layer, operating systems, embedded systems or at the network edge, providing a seamless upgrade from computational security posture to information provable security.

  • The high throughput, low cost of upgradation and ease of integration with the existing set up makes this a very cost-effective and simple-to-deploy solution over the existing infrastructure.

 

  • The Qosmos™ architecture is designed to be scalable, provides load balancing, and has active failover.

Case Studies