Ready to Maximize Model’s Accuracy with Synthetic Data?

NeuTigers’ AI Synthetic Data platform lets you generate a synthetic data twin (having the same probability distribution) of your real data for:

  • Completing your real data with synthetic data in order to train your model more accurately.
  • Anonymizing your data.

Yes, I want Generate Structured Synthetic Data.

Get access to a free trial version of our Synthetic Data generation platform and start training your ML Model on Synthetic Data from tabular numerical data samples.

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Synthetic Data

Block diagram of the NeuTigers DNN synthesis framework



NeuTigers synthetic data engine reduces the need for labeled data up to 83%.



Improves model output accuracy despite using a smaller sample size during the learning phase. The performance of machine learning models are enhanced by training on synthetic data in place of the real data.



Synthetic data can be used to train and advance machine learning models when limited data is available.

Synthetic Data Generation

A catalyst for your business model innovation

Training a machine learning model with real-world data is often tricky; either because the data available must be kept private, or gaining access to such data is expensive and requires a lengthy process or simply because the data isn’t available.

Synthetic data provides the same probability distribution as real training data sets.

A neural network trained with both synthetic and real information is so accurate that it makes big data less relevant. Now, with our free trial version, you can try to generate synthetic data on your own!

Learn more about NeuTigers’ Deep Learning Model Optimization platform.


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