Infrastructure

Cyber-attacks are rising by 300% yearly, and ransomware attacks are increasing to $5B annually. The ability to embed AI-enabled cyber security algorithms into edge devices will be a foundational pillar for next-generation infrastructure operators. MicroAI provides an unprecedented solution for Infrastructure security. Advantages include:

• Broad Threat Detection

  MicroAI’s ML-enabled security algorithms detect and protect against a broad spectrum of cyber-attacks, including Zero-Day, Ransomware, DDoS, and more.

• Consistent Monitoring

  Unlike other solutions, MicroAI does not rely on constant connectivity to function. Connectivity issues do not impact cyber-security monitoring.

• Faster Threat Detection

  MicroAI can detect security threats and intrusions up to 300x faster than traditional security solutions. Legacy solutions can take weeks to detect an attack. MicroAI provides notification in minutes.

MicroAI provides an Edge-native AI solution for integration of smart devices, performance optimization, and cost reduction. Tangible advantages include:

• Flexible/Scalable Machine Learning

  Unique architecture that enables execution of proprietary ML algorithms across a wide range of smart assets (data centers, containers, switches, routers, low-powered edge devices, visualization tools, etc.).

• Centralized End-to-End Solution

  Uniform technology that powers the entire technology stack, resulting in faster time to market and a more powerful competitive position.

MicroAI provides industry-leading Edge-native AI solutions that provide next-level data transmission and cost management benefits.

• Higher Efficiency

  MicroAI significantly improves data transmission efficiency by removing the need for labeled data and by providing training at the device level instead of in the cloud.

• Broad Device Support

  A broad range of support for RTOS, Android, and iOS devices as well as devices with no operating system.

• Endpoint Capability

  MicroAI can be embedded into low-powered, low memory devices at the endpoint (i.e., Cortex M-class MCUs).

• Lower Data Costs

  By collecting and processing data at the point of origin and eliminating the need for cloud processing and storage, MicroAI reduces data costs by 70 to 80%.

MicroAI has the unique ability to provide real-time performance observability into an individual machine or into large groups of assets within the typical infrastructure ecosystem. Deep observability that provides:

• Centralized Data Management

  Data produced by groups of assets is managed from a centralized location. This improves the speed and reliability of data insights and actionable alerts.

• More In-Depth Health Scores

  Depending on configuration, MicroAI can either generate health scores for each individual asset, or a single health score for the entire infrastructure ecosystem.

• Light and Flexible

  MicroAI 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 asset environments.

• Predictive Analytics

  Operational excellence requires not only knowledge of what is happening now, but insights into potential future developments. MicroAI provides the deep learning that is required for true predictive analytics and insights. Moving from reactive to predictive asset management.