Understanding the available hardware and software options and matching these to Edge AI use cases and applications requires a deep understanding of embedded systems.
Our extensive knowledge of embedded systems and AI technologies makes us ideally placed to help you navigate the challenges and help you deliver a successful solution.
The Edge AI Software market size is projected to reach USD 3363.7 Million by 2026, from USD 713.4 Million in 2019. Edge AI is the combination of Edge Computing and Artificial Intelligence. Machine Learning (ML) algorithms are processed locally on an edge device rather than in the cloud or remote data centre.
The algorithms use the data generated by the devices themselves, enabling them to make decisions in a matter of milliseconds. There are almost no limits to the potential uses of Edge AI from smart vehicles, homes, devices, buildings, cities, manufacturing, and more.
Lower latency
Transferring data to the cloud and back to the device takes time. Edge AI eliminates the latency, particularly important for applications that require much quicker response times, such as in smart vehicles.
Real-time analytics
Edge AI enables almost real-time analytics, taking a fraction of a second. For time-critical situations this can be crucial and potentially lifesaving.
As a tried and trusted technology innovation partner, we can help manage your risk and get you to market faster.
Our experienced solution architects can help you navigate common pitfalls to manage risk and get to market faster.
When selecting an AI processing solution, it’s important to consider hardware and also AI software frameworks, as both can impact the capabilities which can be supported.
To help you choose, we’ve created a high-level guide of market options.
There are several open-source AI frameworks on the market. Their capabilities and characteristics vary considerably with performance, coding language, pre-trained models, commercial support and licensing terms.
To find out how these AI frameworks compare, we’ve developed an at-a-glance guide.
What makes the combination of cameras and edge AI so compelling?
Why it’s happening now? and how to start planning your camera and AI project.
We have expertise in chip-to-cloud systems with a deep understanding of security, compliance, device management, analytics and user interface.
We’ve built strong, long-term relationships with providers in the Pay TV, media and OTT industry, helping them become leaders in their field.
From research and strategy to development, compliance, scale and production, we’ve helped clients to avoid pitfalls and get to market without delay.
We’ve accumulated experience in software and hardware design, including embedded and cloud solutions, to deliver intelligent devices and systems.
Our thoughts, ideas and views as well as in-depth technical papers. Explore our insights, get to market faster and make your digital ambitions a reality.
Articles
As organisations scale up from limited trials involving thousands of devices, to hundreds of thousands, the total cost of the offering can spiral upwards, out of control.
Articles
It’s estimated there’ll be over 30 billion active IoT devices in 2025, up from 12 billion in 2020. This dramatic growth is mirrored in the […]
Guides
In the case of AI, big is not always better. This article explores the benefits of Edge AI and making smart choices to get started.
