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Neuton.AI

San Jose, United States (US) · Information Technology

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Data quality

Complete · Accuracy

#Artificial Intelligence

#Machine Learning

#AutoML

#Data Science

#Automated Machine Learning

#TinyML

#iot

#Smart Sensors

#Embedded

#programmable sensors

Neuton.AI is a Information Technology company based in San Jose, United States (US), founded in 2021, with 20-30 employees. Neuton.AI's profile is verified on Enterprise League.

Overview

Neuton.AI – a no-code Tiny ML platform. Neuton.AI was designed to help users automatically build extremely Tiny ML models of optimal size and accuracy, and embed them into any microcontroller, even with 8-bit precision. Neuton's models are extremely compact. Up to 1,000 times: • smaller • have fewer coefficients • demonstrate faster inference in comparison to TensorFlow and other frameworks. Evaluate benchmarks https://neuton.ai/frmwrk#benchmarks Our team of data scientists has created a unique neural network framework Neuton, which is the “brain” of our platform. The framework is based on the neuron-by-neuron model creation principle which allows users to • automatically create models of optimal size and accuracy • avoid any manual search for neural network parameters • exclude the need for model compression, quantization, and pruning after its creation • build incredibly compact models, ready for embedding into microcontrollers Neuton models maintain all original characteristics, without any reduction of accuracy. Neuton does not reduce the model size after its creation. Read about our framework: https://neuton.ai/neural-network Use our service absolutely free of charge Build your first extremely tiny ML model with Neuton to make your edge device intelligent: https://login.neuton.ai/

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Contact Details

support@neuton.ai

San Jose, United States (US)

Founded

2021

Employees

20-30

Categories

Keywords

#Artificial Intelligence

#Machine Learning

#AutoML

#Data Science

#Automated Machine Learning

#TinyML

#iot

#Smart Sensors

#Embedded

#programmable sensors

Awards

• 2026 OpenSee all

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