Building upon the capabilities of MicroAI AtomML, MicroAI AtomML+ provides edge-based intelligence and observability across multiple devices and machines within an IT or OT asset ecosystem. AtomML+ is a proprietary machine learning (ML) platform that aggregates data from device and machine sensors to create behavioral profiles and health scores at the group level and the individual asset level. Key Features include:
AtomML+ is an agentless technology that collects and streams asset data from multiple endpoints into one centralized location.
Machine learning that is designed specifically to run on devices and machines with limited memory and compute capacity such as Cortex A class MPUs. It can also run on other standard architectures, including: X86, RISC, MIPS, etc.
AtomML+ has the unique ability to provide real-time performance observability into an individual machine or into large groups of assets within the IT or OT environment.
Multivariate analysis is performed across large volumes of input channels to generate predictive analytics related to performance and maintenance.
AtomML+ processes data at the edge, vs in the cloud, reducing overall data handling cost by 70 to 80% and eliminating problems associated with data latency.
AtomML is designed to be embedded into a single IT or OT asset while AtomML+ provides the inbuilt scalability to be applied to an ecosystem of assets. Comparative features and applications include:
Embedded ML engine for individual asset optimization
Edge-based ML engine for optimization of groups of assets
Live data is leveraged from a variety of devices...
Fully automatic tuning of the AI model(s)...
Real-time, on-demand, health scores provide...
Embedded ML algorithms learn the normal operating...
The embedding and training of intelligent workflows...
High-speed processing of historical asset performance...
Through accurate identification of root cause...
AtomML+ enables deep observability and multi-spectrum predictive analytics within complex IT and OT infrastructures. AtomML+ provides AI / ML derived actionable insights, at the machine, factory, and enterprise levels. Asset ecosystem optimization advantages that include:
Data produced by groups of assets is managed from a centralized location. This improves the speed and reliability of data insights and actionable alerts.
Depending on configuration, AtomML+ can either generate health scores for each individual asset, or a single health score for the entire IT or OT asset ecosystem.
AtomML+ is an agentless-based platform that requires no external software processes and is less reliant on development of customized application code. AtomML+ can be deployed in a wide range of IT and OT ecosystems.
Operational excellence requires not only knowledge of what is happening now, but insights into potential future developments. AtomML+ provides the deep learning that is required for true predictive analytics and insights. Moving from reactive to predictive asset management.
Intelligence that is reliable, immediate, and cost-effective is the key to achieving new levels of operational excellence within any IT or OT environment. AtomML+ brings the latest in edge-based, agentless, AI technology to bear on operational excellence. Demonstrable benefits include:
A 15% improvement in OEE (overall equipment effectiveness) can equate to a 17% increase in productivity. An operation producing $60M worth of products can increase their output to ~ $70M.
Edge-based intelligent workflows that optimize the performance and efficiency of every critical process, interaction, or transaction across the IT or OT business enterprise.
Unlike cumbersome, legacy, AI solutions, AtomML+ can be deployed and providing value with a couple of weeks as opposed to several months.
A centralized, holistic, cost-effective, agentless AI ecosystem that delivers ongoing optimization and intelligent governance of the entire IT or OT infrastructure
AtomML+ trains advanced security algorithms directly into the devices, machines, or processes within the IT or OT infrastructure. AtomML learns the normal state of asset behavior and provides early-stage detection of profile deviations caused by cyber intrusion. Comprehensive cyber-security that delivers:
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