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Only platform which aligns gracefully with an engineer's mental model

Allows OEM to scale value added offerings across varied equipment classes

Out of the box equipment sub systems and fault modes enabling faster time to market

Advanced diagnostics algorithms for equipment health episode detection

Asset centric grey box models - engineering + statistics + heuristics based machine learning

Action oriented real-time nanoapps machine tweets

Pre-built machine diagnostics tests

Automated predictor ranking

Integration with internal systems workload based stores

Intelligence at the edge

Multi dimensional conditional probability algorithms for fault detection

Automated economic loss estimation,performance bench marking and baseline generation

Persona specific user experience

State of the art and secure lambda architecture powering Cerebra

Finely balanced machine intelligence at Edge and Cloud

Superparser noise vs. signals

Ability to machine learn new signals from billions of machine events

Ability to have asset and process context

Ability to triangulate signals across fragmented data pools - Historians, SCADA, PLC, Maintenance systems, Ambient conditions