
Accelerate AI on Edge
A Simple & Comprehensive Platform to leverage AI capabilities for Edge


AI on Cloud
Challenges of AI on cloud that necessitates disruptive innovation for AI on Edge solutions
Increasing Costs
With the exponential increase in data and workloads demanded by AI deployed on cloud, it increases the demand for more infrastructure thus, increasing costs.
Privacy Issues
Cloud poses risks to privacy. Enterprises and individuals may not be willing to upload confidential data on cloud like health data, private data, etc.
Connectivity Issues
Connectivity issues are a big challenge for AI applications that are highly dependent on cloud. Network issues may delay the processing results.
Latency Issues
Industries requiring real-time data processing like autonomous cars, surveillance of IoT applications cannot afford latency.
Power Hungry
Deep learning models get better with more data, thus becoming more power hungry & heavier than previous models as it evolves in AI capabilities.
Intelligent Devices
As IoT continues to be integral to digital transformation initiatives across industries, it has led to tremendous increase in intelligent devices.

Benefits of AI on Edge
Distributed Intelligence
Edge is the solution
Overcome lack of standardization
Lack of standardization across various hardware available for deploying AI applications makes it difficult for companies to deploy AI on Edge; as every hardware/chip manufacturer has its own way to optimize AI models
Integrate seamlessly with existing frameworks
There are various frameworks and tools are available which are open source, but the integration to them is difficult and is not straight-forward. EDGENeural.ai makes it seamless to integrate across frameworks and tools for Edge application
Rearchitect and optimize models for Edge easily
As a majority of AI today, is cloud-native, it is essential to rearchitect these models so that it can perform efficiently, consume less memory, and is power optimized to work efficiently on Edge. Optimize, and compress AI models to run optimally on small Edge hardware
Accelerate time to market
To build an Edge AI prototype and Edge AI applications, you do not have to invest 6 to 8 months anymore in deciding what hardware to choose, what framework and tools to select. Nor, do you have to spend thousands of dollars in hiring Edge AI developers. Train, Optimize and Deploy in weeks, not in months/years.