Easier and Faster AI for Business!
Leveraging our acceleration solutions and AI application technologies,
SoyNet makes AI easier and faster for your business
Top-Class AI Acceleration Solutions
SoyNet offers a range of light, flexible,
and fast AI acceleration solutions.
A Full Portfolio of Solutions
SoyNet has a full portfolio of acceleration solutions to cover various AI models
in video, vision, time series, natural language, and other data intelligence.
Armed with this full range of solutions, SoyNet assists clients across multiple domains
Time to Market Assistance
No matter how good the AI services you have developed are, their success largely hinges on their timely launch.
SoyNet helps reduce the trial and error time needed to achieve optimization and acceleration,
relieving your time-to-market burden.
S/W based AI Accelerator
SoyNet offers easier and more flexible ways to deliver AI-driven services.
Accuracy matters during the development phase. Inference speed matters even more once service begins. With a C/C++ based high-speed inference engine, SoyNet helps you render services without delay.
Super Lightweight Engine
General-purpose AI frameworks are heavier and run slower than expected for service execution. SoyNet executes AI models without deep learning frameworks such as TensorFlow, PyTorch, and Caffe.
Accelerator for General Model
Your business can be expanded through a combination of different AI models. As an inference software acceleration solution, SoyNet can be used to accelerate various models for image processing, natural language, and anomaly detection.
You don’t need to have a team of top-notch in-house AI specialists to integrate AI into your business. SoyNet delivers high-level APIs, ensuring that your existing application developers apply AI to your services.
Extended Support for Standards
There are a range of standards offered by numerous vendors to help run AI models. SoyNet supports not only NVIDIA CUDA technology but also OpenCL.
Embeddable at the Edg
Demand for AI services comes not only from Cloud- and server-based inference tasks, but also from non-Internet environments like edge computing. SoyNet can be embedded into small edge devices like Jetson Nano, bringing models learnt from the desktop to edge devices.
Don’t hesitate to contact us.
Any comments or suggestions are always welcome.