Maximize data utility and data privacy with AI-powered synthesis
Deep neural network generative models by way of Variational Autoencoders enable the highest degree of realism in your synthetic data. Preserve the distributions, statistical integrity, and complex relationships among continuous, categorical, location, and events data.
Why AI Synthesis
Build effective ML models
Gain confidence in your ML model training with more accurate synthetic data
Answer nuanced scientific questions
Perform analysis on data that provides proven degrees of accuracy and privacy.
Optimize your product and your business
Future-proof complex features and forecast scenarios to drive business decisions.
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Achieve compliance and data governance
Meet the requirements of today and tomorrow’s data privacy laws with the most advanced protection processes available.
How we synthesize
Deep neural network generative models
Work across continuous, categorical, and location data
Time series data over interdependent rows
Extensive database coverage
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What our customers are saying
“Until you’ve tried to synthesize data, you don’t realize how important it is to find someone who does it for a living.”
“Nothing that we tried in-house is comparable to what we’re doing now with Tonic. It’s a game changer.”
“As more teams become aware of Tonic here at Alegeus, more of them want access to the data it's generating”
