AI software infrastructure for enterprises
Enterprise-grade AI software infrastructure that enables a simpler, faster, and more scalable integration of AI/ML capabilities into Java-based enterprise applications.

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.
Simplified. Accelerated. Scalable.
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