Create a General-Purpose Generative Model for
Any Dataset

Apply the Synthesized SDK to automatically create a generative model for any datasets to bootstrap data where the density of data is low, automatically reshape data as you like, and even anonymise data for repurposing.
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Automatic On-Demand Generative Models of Structured Data for Any Task

Automatic Data Upsampling and Bootstrapping for Backtesting, Cross-Validation and More with No Hassle

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Data reshaping and manipulation
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Multiple scenarios that allow for thorough model testing
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Unlimited volumes of data on demand
Solving Data Imbalance
Solving Data Imbalance with Generative Models
Automatic data up-sampling and bootstrapping for backtesting, cross-validation and more with no hassle

Comprehensive Data Science Tools to Enable Robust Data Imputation and Increase Model Performance

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Can accurately represent your intended population, resulting in more accurate and robust models
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Automatically generate accurate data points for datasets with missing values or outliers at scale
Imputation User Guide
Imputation User Guide
Comprehensive data science tools

Privacy and Anonymity
at the Core

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Generate required volumes of anonymous data from generative models
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Create models with in-built differential privacy
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Robustness against complex attacks such as linkage attacks and attribute disclosure
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Configure privacy parameters within the SDK to meet your organisation’s needs
Is Anonymization Really Private?
Is Anonymization Really Private?
Privacy and anonymityat the core

Integrates into Everything

Whether you are a data engineer, data scientist or machine learning researcher, the SDK can be easily integrated into your existing workflows for ETL, data preparation and model training. It’s all set and ready to use.
Integrates with Scikitlearn
Integrates with TensorFlow
Integrates with NumPy
Integrates with Pandas

Compare Editions of the Synthesized SDK:

PLAN

Free

PLAN

SDK Solo Edition

PLAN

SDK Team Edition

Unlimited generative models and datasets
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yes
yes
Data scenarios generation (model testing & evaluation)
yes
yes
yes
Data rebalancing
yes
yes
yes
Data imputation (missing values & outliers)
yes
yes
yes
In-built differential privacy guarantees & guidance
Default configuration
Bespoke privacy parameters optimized
Bespoke privacy parameters optimized
Production sensitive data support
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yes
Any private cloud / on-premise self-hosting
yes
yes
Builds for Linux, Windows, MacOS
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yes
Docker image support with pre-installed SDK
yes
yes
Database & SQL support
yes
yes
ETL integration
yes
yes
Fully tunable in-built differential privacy guarantees & guidance
yes
yes
Synthesized UI
yes
Collaboration features
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Community support
Community support
Standard support

Develop with Synthesized

Synthesized Generative Models: 10X the performance, 0 risks
Synthesized's DataOps Blog
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