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.
Increased information security and privacy
With less data moving back and forth to the cloud, there are fewer chances of data being hacked. Using a closed network makes this even harder for criminals to crack.
Scalability
With the growth in connected IoT devices expected to generate 79.4ZB of data in 2025, Edge AI will ensure there isn’t a hold-up when it comes to data transfer, ensuring scalability.
In this rapidly evolving landscape, understanding the trade-offs between the many opportunities is essential. We can support you whatever your current stage of development. Our experience of designing and developing edge devices for the home and other environments can help you navigate the technology landscape from chip to cloud. This experience includes:
Reference Guide
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.
Reference guide
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.
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.
We’ve designed connected home systems with security at heart to protect customers and their valuable content.
We have a proven track record in embedded hardware design, software development and systems integration.
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 connected devices and systems.
