AI on Edge

Decentralize AI

End to end workflow solution, focused on improving the efficacy of AI algorithms and models for Edge devices

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Accelerate AI adoption on Edge

An end-to-end platform enabling AI developers to train, optimize, and deploy blazing-fast deep learning models on any hardware, in a matter of hours!


Accelerate Time to Market


Reduction in cost of development


Accelerate Inference on Edge
Accelerate Deep Learning

New frontier for deep learning models

Accelerate machine learning model performance, with the best accuracy-latency trade-off on any hardware. Train, Optimize and deploy models with impeccable speed.

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Train models from scratch, use a pre-optimised model or your your own model
Optimize inference performance without any accuracy trade-off
Enable continuous deployment seamlessly on any Edge hardware
Accelerating Edge AI adoption

Enabling AI for smarter, faster and efficient Edge devices

EDGENeural is a software defined platform that is modular, unified, hardware agnostic, that integrates the end to end workflow for any AI engineer for any AI application, to build, train, optimize and deploy, across various hardware platforms
Low-Code Platform
Requires minimum set of inputs, and does not require expert coding knowledge to build Edge AI application. Companies can save cost of hiring expensive Edge AI experts or developers.
AI Model Optimization
With the accuracy level bar set at -1, improve model performance without accuracy trade-offs to easily deploy on actual hardware. ENAP retains the model is the accuracy level drops.
Open Platform
ENAP allows you to seamlessly integrate with any third party services without worrying about any tools and platforms you are using and is extensible for any application
Model Zoo
Model Zoo provides a set of pre-trained and pre-optimized model libraries which can be used to deploy any kind of use case for multi hardware and multi-application development
MLOps/ Edge DevOps
Get your new set of data trained, optimized and ready for deployment with effortless MLOps and model management, engineers can manage models and versioning within the platform.
Easy to Use
Train, optimize and deploy edge AI modules with just a single click. Reduce data set training optimizing, and deployment pipeline from months to days or even hours
Hardware Agnostic
ENAP consists a hardware extraction layer, which allows companies and developers to seamlessly switch between hardware, and automatically recompiles for chosen hardware
Cloud Neutral
ENAP is cloud neutral, and can integrate with data sets for any cloud platform or technology, easily migrate from Azure to AWS or vice versa.
Scalable Software Platform
ENAP is architected to be a scalable platform that can be scaled across various edge devices, AI models, and can be trained, optimised and deployed seamlessly.
Collaboration Tools
It’s a collaborative tool, so multiple users or engineers can work towards a single project or a single application
Accelerate AI adoption on Edge

Why EDGENeural AI Platform (ENAP)?

End-to-End software stack is the secret behind AI on Edge adoption

End to End Workload Processing
End to End Workload Processing
Process AI and Non-AI work loads on the chip
End-to-End AI software development with model lifecycle management
Extensive Edge AI Software Platform
Extensive Edge AI Software Platform
Supports existing libraries
Pre-Built Optimised Models for chip
Model Optimisation
Pruning / Compression
MLOps / Edge DevOps
MLOps / Edge DevOps
Model Lifecycle Management
Model Benchmarking
Federated Learning