Deep asset observability at the edge. MicroAI brings real-time observability to any type of IT or OT device or machine. From low-powered edge devices to high-powered servers, MicroAI delivers deep insights into asset performance and security.
Observability is about generating actionable insights from the data generated by assets within an IT or OT infrastructure, insights that enhance the operation’s ability to maximize OEE (overall equipment effectiveness) and security. Observability goes well beyond static monitoring and logging.
Learning the normal behavior of an individual asset or a group of assets.
Utilizing embedded machine learning (ML) algorithms to provide deep insights into real-time performance and health of assets.
Recursive analytics that produce predictive insights into future asset health and maintenance requirements.
Embedded intelligent workflows that deliver insights and alerts to designated stakeholders.
Many critical assets (machines, devices, network equipment, etc.) lack the deep observability required to produce deep insights into performance, health, and security. The lack of deep, asset-centric, AI-enabled observability creates a host of problems within the asset ecosystem:
Asset ecosystems are plagued by a host of problems resulting from legacy solutions that watch but that do not actively learn. This observability shortfall produces numerous barriers to operational excellence.
The lack of deep asset observability inhibits the gathering of insights into the effects of varying environmental conditions and the impacts on assets that are similar in design but that perform dissimilar functions.
The absence of deep, real-time, asset observability creates a barrier to the immediate detection and notification of an asset performance anomaly.
The inability to generate timely, accurate, actionable, predictive analytics is a prohibitive limitation in fully optimizing the performance and security of mission-critical assets.
A typical edge device or compute unit -VMs, containers, machines – can produce 100 MB to 1 GB of telemetric data daily. The high cost of data transmission can be a prohibitive factor. Scaling and processing terabytes of data is increasingly costly for operations that rely on cloud-based infrastructures. Challenges include:
Traditional monitoring solutions are not equipped to manage large volumes of asset data, requiring additional external—costly— support.
No ability to quickly discern critical data from non-critical data results in costly processing inefficiencies.
Heavy reliance on cloud infrastructures creates prohibitive cost burdens due to data latency, management inefficiencies, and data transmission.
MicroAI is redefining asset observability by moving observation closer to the asset and by providing the intelligence to maximize that observability. MicroAI is the only technology that provides local AI model training and observability. Technology that provides:
MicroAI offers a powerful AL/ML platform that covers the entire spectrum of enterprise infrastructure observability. MicroAI’s breakthrough technology enables the observability required to maximize OEE and attain new levels of operational excellence. Differentiators that include:
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