Empowering the
Java Ecosystem for AI

Deep Netts is an AI Development Platform Company that revolutionizes the way organizations leverage machine learning models, while contributing to modern Java’s role in AI.

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AI Development Platform for Java

Deep Netts platform accelerates AI adoption by simplifying development, integration and deployment, making AI more accessible and efficient for Java-based enterprises.

Visual AI Builder

Visual tools simplify AI model development with a drag-and-drop interface for data preprocessing, model training, testing, and debugging. They enable rapid iteration, experiment tracking, and efficient model refinement and optimization.

Deep Learning Java Library

A high-performance, pure Java implementation of deep learning algorithms featuring an intuitive API, for easy integration and deployment of AI models in production environments.

//create an instance of a neural network using builder
FeedForwardNetwork neuralNet = FeedForwardNetwork.builder()

.addInputLayer(numInputs)
.addFullyConnectedLayer(1024, ActivationType.RELU)
.addOutputLayer(numInputs, ActivationType.SIGMOID) .lossFunction(LossType.CROSS_ENTROPY)
.build();

//set training settings
neuralNet.getTrainer().setStopError(0.02f)

.setStopEpochs(300)
.setLearningRate(0.001f);

//run training to build the model
neuralNet.train(dataSet);

Explore Real-World Use Cases

See how companies like yours run AI models with Deep Netts — entirely in Java.

Fraud Detection

Detect credit card fraud in real-time with a pure Java AI pipeline.

Cloud Cost Optimization

Optimize latency and throughput using predictive models running natively on JVM.

Scientific Computing
(Jefferson Lab)

Accelerate particle tracking in nuclear physics with fast, scalable AI.

Quality Inspection

Automate defect detection in manufacturing with high accuracy, no Python overhead.

Simplified. Accelerated. Scalable.

easy to use

Easy to use

Machine learning development tool with step by step visual expert guide in integrated environment for end to end ML development process.

accelerated

Accelerated development

With Deep Netts developer friendly, pure Java deep learning library and tools for building and testing machine learning models.

Rapid

Rapid deployment

Seamless integration of ML models into your Java native applications and deployment to production.

Cost

Cost effectiveness

Deep Netts enables utilization of existing developer resources instead of hiring additional experts, decreasing employee costs.

Scalable icon

Highly scalable

Deep Netts enables easy deployment to a large number of devices in heterogeneous environments.

Privacy & Security

With Deep Netts you own and control data, you own models. The solution enables secure Java integration.

Why choose Deep Netts?

Empowering developers and businesses towards AI/ML by enabling faster learning and easier deployment with two key features Java-Native Deep Learning Library and ML Ops Tool with explainable AI

01

Easy to get started

The platform is designed to be user-friendly, making it easy for developers to begin using it. It provides visual tools that allow users to build ML models without requiring extensive AI knowledge.

02

Simple integration and distribution of models

Designed and built for deployment into Java native environments. The platform offers straightforward integration and distribution options for the created models. Deep Netts solution enables easy, cost and resource efficient integration for machine learning.

03

Supported by Java community

Deep Netts provides reference implementation of the JSR 381 standard, supported by Java Community Process. JSR381 standard determines how Java applications talk to AI, and how Java developers approach solving ML problems.

What Our Customers Are Saying