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Pre-trained.  Accelerated.  AI. 

Accelerate Your Edge AI deployments with Secure, Scalable, Fast, and Fail-safe Edgeble Pre-trained AI Accelerator Platform.

AI/ML Accelerators in the form of Neural Processing Units (NPU) is designed to compute high-performance parallel
AI workloads for high response time and low latency.

Edgeble AI is one of the first AI-centric solutions providers engineered in deploying AI Acceleration principles at the edge.

Our unified architecture enables companies to develop Edge AI-enabled solutions once and deploy them everywhere starting from consumer sector to robust industrial sectors.

General 
CPU
Computation

Edgeble 
Neural 
Acceleration

Example of How Edgeble Neural Acceleration on Perceptron (P) Neural

AI/ML Accelerators play a vital role in the parallel computation of machine learning algorithms however deploying them at the edge requires a reliable and fast set of challenging computing designs with integrated software tools.

Edgeble has engineered an Edge AI platform stack that will accelerate the time-to-market for a world of companies that are producing high-grade Edge AI-enabled solutions. The architecture was designed with scale-ready Neurally-accelerated computing modules with pre-trained open software inference deployment models.

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Neurally Fast

Edgeble Neural Compute Modules are built on top of high-Speed and low-latency modeling Neural Accelerated System On Chips. These accelerators are highly responsive and operated with trillion operations per second speeds of 2TOPS, 6TOPS and so. on.

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Ultra Vision

Image Signal Processing (ISP) is the heart of deriving precise and efficient computer vision. Edgeble Neural compute modules are built on hardware-driven ultra codec algorithms for real-time processing of 4K and 8K with optimized GPU workloads.

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Pre-trained Inferences

Deploying the accelerators at the edge would be a challenging task however usage of these accelerators is customer-centric inference modeling. Edgeble platform has a generic solution to handle custom model management via pre-trained inferences.

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Open Source deployment

Edgeble platform stack has a set of tools in each stage on top of open-source Linux with secure container-based deployment management. This makes customer engineering time reduced by almost ~55% with no license vulnerabilities.

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