Machine Intelligence – Making machines more transparent
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Machine Intelligence

Machine Intelligence – Making machines more transparent. An embedded AI platform that provides deep insights into machine and device performance. Full transparency, all the time.

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What Is It?

Powered by MicroAI’s core technology MicroAI AtomML™, Machine Intelligence represents a paradigm shift in the optimization of the performance and security of machine assets. Mission-critical machines within the manufacturing, telecom, automotive, and infrastructure segments can be transformed from opaque entities into assets that are fully transparent. This transparency delivers deeper insights that enable active fine-tuning of performance. Transformational areas of impact include:

Enabling Predictive Maintenance with Endpoint AI

MicroAI’s Machine Intelligence provides the endpoint intelligence to power the transition from static preventive routines to predictive capabilities that transform asset maintenance.

Machine Intelligence Features

Despite advances in Industry 4.0 technologies, most industry segments are still hampered by a lack of full transparency into their machine assets. Machine Intelligence solves the problem with a powerhouse of AI-enabled features:

  • Endpoint-Based Performance Monitoring

    Enables real-time machine-centric performance observability and reporting

  • Machine Endpoint Intelligence

    Provides transparency into current machine health and facilitates a transition to predictive maintenance

  • Historical Trend Analysis

    Intelligence-based prediction of future machine behavior and productivity

  • Intelligent Workflows

    AI-enabled workflows ensure that the right information is delivered to the right stakeholders at the right time

  • Machine-Specific Security

    Provides faster detection and mitigation of Zero-Day attacks against machines and data


Machine Intelligence brings real-time observability to any type of machine or industrial  device. Moving beyond static data collection, embedded intelligence delivers the deep insights needed to fully optimize the performance of a single machine or an entire machine ecosystem. Capabilities that include:

  • Dynamic Learning

    Embedded AI an ML algorithms learn the normal operating behavior of an individual machine or a group of machines. Deep federated learning provides the accurate baselines required to detect performance anomalies of any size or duration.

  • Endpoint Observability

    Intelligence embedded into the machine endpoint provides deep insights into real-time performance, health, and security. Active learning delivers levels of observability that have not been available with traditional AI solutions.

  • Recursive Analysis

    Multidimensional behavioral algorithms produce recursive analysis, training, and processing. This enables a continuous evolution of the AI model that takes place directly on the endpoint. Recursive analytics produce predictive insights into future machine health and maintenance requirements.

  • Insight Mining and Distribution

    A centralized visualization engine provides continuous observability into the status of connected devices and machines. The embedding and training of intelligent workflows automate the process of performance alert notifications and implementation of rapid mitigations.

Predictive Maintenance Demo

Business/Operational Value

Machine Intelligence delivers tangible value across the entire business enterprise. Business and operational stakeholders will benefit from several insight-powered advantages, including:

  • OEE Improvement:
    Observability and insights that overpower stagnant OEE performance. Machine intensive industries will be able to break the 70% OEE barrier and to realize associated competitive advantages.
  • Increased Output:
    Machine outputs that are fully optimized, more reliable, and more predictable. Production planners and schedulers have powerful advantages in the ability to plan and schedule based on machines that are fully transparent and that produce real-time health scores.
  • Higher Quality:
    More rapid detection of performance deviations reduces the impact of sub-par performance. Performance anomalies are quickly detected, communicated, and mitigated. This results in higher quality, reduced rework, higher reliability, enhanced predictability, and greater customer satisfaction.
  • Enhanced Cyber-Security:
    A Zero-Trust cyber state that provides superior protection of machines and the data that they produce. Greater protection against crippling Zero-Day attacks and the ability to achieve a predictive cyber-security footing.
  • Reduced Cost:
    Reduced cost associated with machine maintenance, productivity loss, waste, rework, service disruptions, and customer loss. Tighter control of CoGS that produce market-leading bottom lines.

OEE Improvement

Increased Output

Higher Quality

Enhanced Cyber-Security

Reduced Cost


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