Edge AI Development Services

Embien offers its expertise for developing Edge artificial intelligence enabled systems that is proven across application domains

Use our high-accuracy, small-footprint, high-performance, ready-to-deploy models on custom built embedded AI accelerated hardware platforms

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Edge artificial intelligence Offering

Embien, for the past few years, has been in the forefront of the Edge AI revolution. Backed by sound knowledge in embedded systems, our AI designs are highly optimized and efficient. Our customers include industry leaders in automotive, industrial, medical and consumer electronics. Our engineers have developed the capability to run even the complex algorithms on resource limited systems and manage them remotely. Our team is knowledgeable of AI/ML models and uses the right tools and technologies to provide the best possible output.

Our team can also design custom hardware capable of running AI on the edge as per the customer business requirements. The designs can incorporate advanced GPU architectures and neural processors along with necessary memory modules to accelerate algorithm execution. We have even developed FPGA based solutions and FPGA accelerated design to take advantage of parallel processing performance on the Edge artificial intelligence systems.

Why Embien for Edge AI Development?

Real Time Decisions

Our models are optimized for low-latency and high performance to enable faster processing and decision making

Optimized for Embedded

Get the right embedded ai hardware platform in place and run the right algorithms fine-tuned for the edge

Domain Expertise

Leverage our domain knowledge spanning few decades in all major industries to choose the optimal solution

Ready to use models

With our vast library of hundreds of pre-trained models, quick start your artificial intelligence transformation

Embedded AI Systems

Embien has been enabling Edge AI Development with all the leading silicon vendors such as Nvidia, Renesas, NXP, Qualcomm and TI. Our team has also developed advanced Edge AI solutions on FPGAs from Intel and Xilinx. In all these cases, the implementation is fine tuned to take advantage of the features provided by the underlying platform. Some use cases we have demonstrated include.

Sensor Fusion for IoT Edge device
Predictive maintenance of industrial systems
Driver Monitoring System
Automotive Driver Rating system

>We have specially developed skills for CUDA programming to accelerate embedded AI performance on NVIDIA systems. We can also port Python algorithms to C++/CUDA code based to help optimize them and increase security.