Edge Intelligence

Infuse the power of Edge Computing

Edge intelligence is referred to as a distributed computing paradigm where data is collected, analyzed and interpretation is drawn to capture it in content delivery networks. Modern edge computing software is beyond the power of artificial intelligence or machine learning as real-time data aggregators are used in them.
The new commercial edge computing services empower machines to make decisions based on locally harvested data instead of sending it to centralized cloudlets. It is a game-changing technology of deploying AI and ML on the heterogeneous computing system.

Common industry challenges

Are you not able to embed devices with the desired amount of hardware on the full-scale data center?
Several mobile edge computing environments are restricted from the standpoint of technical computing. Especially, when you can’t embed devices with hardware fitting on a full-scale data center, thus edge devices are essential to do the job.
Do you want to reduce your human IT deploying cost?
Edge programs often have logistical and operational cost problems in the deployment of human IT resources. Now, companies can’t appoint dealer locators on every edge location. With the proper deployment of ubiquitous computing technology, latency and operating limitations of edge programs can be eliminated.
Are you always worried about the security of your data center?
Security is the key issue including the secure communication of the data center to edge while making sure the security at both ends. With the SASE (Secure Access Service Edge) security features, the edge devices' ability to find and track cyber attacks become highly strong.
Are you facing problems in creating a unified architecture to target edge as well as traditional data centers?
It is a major challenge as many edge applications need to be deployed across other data centers too. This creates a complicated and unmanageable syntax of codebases and deployment processes. With a serverless architecture pipeline, these architecture silos can be eliminated.
Is lack of skilled professionals an issue for you?
In some environments, skilled professionals are not available to manage work regularly. An unskilled professional won’t be able to handle sharp functions of fog computing such as facial recognition algorithms, pixel streaming, application updates, deployment of additional devices and so on. But, the sophisticated edge technology can handle all the essential features perfectly.

Benefits of Edge Intelligence

01.
Reduce Latency
Some applications require immediate insight and control. For instance, online shopping carts need to be updated immediately when buyers tap on the buy button. Thus, edge technology real-time detection comes into action.
02.
Eliminate Bandwidth Issue
The process of sending big data back and forth to the cloud can be a high bandwidth-consuming task. But, thanks to edge computing, this isn’t the case anymore.
03.
Decreased Cost
Even with the reduction in bandwidth, the process of sending and receiving big data is expensive. That’s why computing the offloading element of IoT of edge technology is highly beneficial here.
04.
Highly Secure
When you have to transfer data across the ocean, it is simply more prone to cyber breaches. By thoroughly processing data at the edge side can reduce the data transfer risk and makes the process highly safe.
05.
Better Reliability
Without the intervention of hackers, the data can easily corrupt on its own. The dropped cell phone calls and broken ad insertion engines are common problems. However, with edge technology a great degree of reliability can be established.
06.
Legal Compliance
When data is transferred crossing the national boundaries, then the laws and corporate policies of the receiver and sender nations need to be considered beforehand. With edge programs, the legal compliance related to data transfer can be handled automatically.
07.
Data-Driven Experience
SaaS services enable users to have a personalized and data-driven experience while improving the application and developing a user engagement and customer satisfaction level.
08.
Predictive Maintenance
IoT edge allows users to enjoy the automated and real-time predictive maintenance environment for better uptime which will eventually lead to enhanced efficiency and profits.

How SynctacticAI connects with Edge Intelligence?

Real-time data-driven decision making is the necessity of businesses to evaluate the factors behind increasing revenue and reducing cost. Sync Learn Edge Computing lets businesses target the variables and features – with just one click, deploy the solution into the production environment to start providing immediate results. Edge Intelligence and Sync Learn are the two perfectly fitted pieces of a jigsaw puzzle.

IoT Solutions

Various pipelines and learning models empower manufacturing, transportation, and other prime industries through the elements of Synctactic’s Sync Learn and Edge Computing offering.

Improved Connectivity

The power to technology providers is availed to sort the problems of latency and increased costs.

Automation

Data sets can be automated by selecting the target variable and defining the goals to run multiple models parallel.

Maximize Customer Experience

The edge communication leads to the maximum customer satisfaction by increasing monetary profits, customizing services, reducing the data churn and helping in finding better capital outlays.

Would you like to implement a Predictive Maintenance Program with SynctacticAI? Our Sync Learn offering enables companies to draw meaningful outcomes from the massive pools of data to transform business efficiency.

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