Predictive and prescriptive analysis of data received from various IoT data sources, including sensor, device, equipment or network enabling the users to take actions in real time on probable anomalies detected.
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90%+ Accuracy with prebuilt ontologies and scalable over time using reinforcement learning.
Inherent Reinforcement Learning algorithms provide improved performance over time with & without human intervention.
30+ probabilistic spatial graph algorithms trained for automated ingestion, fingerprinting and real-time analysis of sensors, smart meters and networks.
Delivers multi-million variable analysis for end-to-end coverage and actionable insights for asset risks, failures and maintenance.
Equipped with a library of 30+ proprietary supervised and unsupervised algorithms designed, trained and tested.
Real-time analysis and alert generation using computer vision and varied visual data sources such as videos and images from internal and external sources.