Edge Devices – IT
Enterprise AI for IT edge devices. MicroAI™ has developed Edge-native AI solutions that deliver higher levels of visibility, control, predictability, security, and profitability for IT edge devices. Minimizing the dependance on cloud infrastructures reduces transmission costs while creating more consolidated command and control of IT edge device ecosystems.
Edge Devices in IT
IT infrastructures utilize a broad array of edge devices (routers, switches, wide area network (WAN) devices, sensors, multiplex devices, and more). Beyond merely providing connection between networks, these devices are now tasked with performing a wide range of critical operational and security functions. In many cases, expectations have outpaced capabilities.
Evolving Edge Device Requirements
IT operators need to expand the capabilities of their existing, and future, edge devices. Competitive viability depends upon it. Those capabilities will need to deliver:
- Edge-based intelligence
- Deeper observability
- Faster Insights
- Predictive analytics
- Improved security
- Reduced cost
Traditional solutions for edge device management will not meet the demands of the increasingly complex and diverse IT edge device infrastructure.
Edge-native AI for IT Edge Devices
The volumes of edge device data are increasing at exponential rates. Processing massive volumes of data in the cloud is inefficient and cost prohibitive. MicroAI brings intelligence and computational power closer to the sources of data. The advantages of MicroAI’s Edge-native AI:
AI and ML algorithms are embedded and trained at the device level. Data is processed locally and autonomously instead of in the cloud.
Critical data is processed locally, at the device, eliminating cloud transmission latency. Analytics produced in milliseconds.
Penetrating insights into the performance, health, and security of the edge device (ability to respond to conditions 400x faster than previously possible).
Recursive analytics that produce predictive insights into future behavior, maintenance requirements, and productivity. Insights that power the evolution to a predictive device management state.
Reduced cloud dependence directly equates to massive reductions in data costs. Savings in the hundreds of thousands of dollars.
Improved Edge Device infrastructure
Device-specific and device ecosystem intelligence that enables quick identification and corrective action on devices that are performing below their normal state.
IT Edge Device Cyber-Security
IT infrastructure are under constant threat of Zero-day cyber-attack (Ransomware, DDoS, Phishing, Cloud Breach, etc.). These attacks can have far reaching and long-lasting implications.
Cyber intrusions can cripple the performance of edge devices for extended periods of time.
Loss of Data
Critical asset and operational data can be held for ransom or permanently lost.
Cyber-attacks can expand to penetrate external targets (partners, suppliers, customers).
Large-scale attacks can degrade customer confidence, reduce revenue, damage market reputation, and expose the operator to legal risks.
Interested in how MicroAI can benefit you?
MicroAI AtomML brings big infrastructure intelligence down into a single piece of equipment or device.