Do more, with less

Optimizing AI for lightning-fast speed and cost efficiency

Speedup your model by
0x
Reduce memory by
0x

Affordability

Deploy AI on cost-effective hardware.

Speedup your model by
0x
Reduce memory by
0x

Privacy

Safeguard sensitive data with on-device computing.

Reliability

Run AI models on-device, independent of internet connection.

Flexibility

Deploy on PCs, smartphones or even microcontrollers.

Use case

EdgeGPT

Low-cost

Fast natural language processing using consumer-grade hardware.

Learn more

Data privacy

With on-premise computing, you don't need to worry about your sensitive data being compromised. Your data never leaves your control.

Learn more

Customizable

Whether it's confidential data analysis, customer support or a different application, EdgeGPT can be fined-tuned to your unique needs.

Learn more

EdgeGPT

What's so special about EdgeGPT?

As EdgeGPT, I am optimized for both speed and efficiency, enabling me to process large amounts of text data rapidly while utilizing minimal computational resources, even on consumer-grade hardware. This makes me a cost-effective solution for businesses and individuals who require high-quality natural language processing services but do not want to invest in expensive infrastructure. Additionally, for clients who require processing of sensitive and confidential data, I can be self-hosted and offer a private instance for secure and exclusive data processing, ensuring data privacy and control.

What applications can EdgeGPT be used in?

As EdgeGPT, I am particularly good at natural language processing applications such as language translation, sentiment analysis, chatbot development, content creation, data analysis, and customer service automation.

Train

Your model with your favorite framework

John's Cat

Cat eating

John was afraid his cat wasn't eating well. So he trained a model to track his pet's eating habits.

Model collection

Want to quickstart right away? Skip training and pick one of our pre-trained models and deploy EdgeAI in under 5 minutes.

Learn more

Input data

We support any input data, from 2D images to 1D time series (e.g. audio or biomedical data)

Learn more

Compatibility

BinedgeML supports models trained in the most popular frameworks such as TensorFlow, PyTorch and Jax.

Learn more

Unlock the potencial of your AI

Optimize

Your model with EdgeCompiler

Extreme quantization

Modern AI models have millions of parameters, which makes them hard to deploy in tiny devices. We overcome this by adopting Binary Neural Networks (BNNs).

Learn more

Optimized compilation

Our compiler performs several optimization techniques on the model, allowing it to run even faster and with fewer resources.

Learn more

Relative Metrics

Performance

Memory used

Energy consumed

EdgeRuntime

TensorFlow Lite

John didn't want to buy an expensive GPU, spend dozens of dollars in electricity or subscribe to a cloud computing service to run his model.

Deploy

Real-time fast AI with EdgeRuntime

binedgeai.py

import BinedgeML.EdgeWare as EdgeWare

model = loadModel()

while True:
    input = getInput()
    predictions = EdgeWare.inference(input, model)

Now, John gets a notification every time his cat goes for a meal with a simple, inexpensive and power-efficient system.

Ultra-low power

Our runtime software is so efficient, it can even be deployed in a tiny device powered by a small solar cell.

Learn more

Easy integration

Deploy to your ARM micro-controller, RISC-V CPU, or even to your x64 PC using a single line of code through our Python or C EdgeRuntime API

Learn more

Speedup your model by0xReduce memory by0x

Affordability

Speedup your model by0xReduce memory by0x

Privacy

Reliability

Flexibility

Use case

EdgeGPT

Low-cost

Data privacy

Customizable

Train

Your model with your favorite framework

Model collection

Input data

Compatibility

Unlock the potencial of your AI

Optimize

Your model with EdgeCompiler

Extreme quantization

Optimized compilation

Deploy

Real-time fast AI with EdgeRuntime

Ultra-low power

Easy integration

Speedup your model by
0x
Reduce memory by
0x

Speedup your model by
0x
Reduce memory by
0x