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The fastest way to create trusted data

Create high-quality data for machine learning, application development and testing with easy-to-use config files.
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Synthesized SDK
Creates tables for machine learning and analytics.
pip install synthesized
Synthesized TDK
Creates databases for application development and testing.
tdk -c config.yaml
Deutsche BankUBSalt.bankFinancial Conduct AuthorityClarity AINVIDIA Inception
Trusted by data teams at the world’s leading companies
01
Specify requirements
Write data requirements in a YAML config file for a database or using Python DSL for a dataset.
02
Create workflow
Create a data transformation job, check data categorization and access rights.
03
Run job
Run job as part of CI/CD or data pipeline to create data in the destination that meets the requirements.
Why Synthesized

Create data with Synthesized to:

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Adopt DevOps for your database management

Make your database provisioning cloud-native using our database generation, masking and subsetting engine that runs in Kubernetes.
tdk
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Automate test data management with the power of AI

No more manual configuration of complex data transformations. Use modern AI-driven techniques for data masking and generation.
tdk
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Facilitate cloud migration

Synthetic high-quality database generation for functional validation, performance, and integration testing in the cloud for Snowflake, GCP, Amazon Redshift, and Microsoft Azure.
tdk
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Increase market value of existing data

Generation of high-quality synthetic data for data monetization with third-party firms that preserves statistical properties of original data and is free of sensitive PII/SPI data.
sDK
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Shorten time to data

Create reusable data transformation workflows to shorten data collection lead time. Iteratively set up and test ML pipelines with Airflow, GCP Cloud Composer, Dbt, Spark, and other ETL tools instead of waiting for the lengthy original data access procedures.
sDK
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Faster outcomes

An API-first approach to create high-quality data

Full automation

DevOps-friendly API-driven framework to create tabular data and databases in minutes using YAML config files and Python DSL.

Improved data quality

Our machine learning models learn statistical properties in a table and across tables to help create high-quality data, often better than production data.

Guaranteed compliance

"Data as Code" approach enables you to codify complex compliance requirements into concrete data transformations.

Fast and easy deployments

Simple API to integrate into your CI/CD or data pipeline, both on-premise and cloud. Supports all relational databases and data governance platforms (BigID, Collibra, Zaloni) and deployments using Kubernetes, OpenShift, and Docker.
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Cloud

Create production-like data in your cloud tenant

Deploy instantly, supercharge effortlessly, and accelerate initiatives with seamless cloud marketplace integrations. “Data as Code” approach makes it easy for anyone to be a data engineer.
MicroSoft Azure
Run our products on Microsoft Azure.
Azure Marketplace
GCP
Run our products on Google Cloud.
Google GCP
AWS
Run our products on AWS.
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On-premise

More options

Run SDK and TDK locally.
Synthesized SDK
Self-service — Free
Synthesized tDK
Self-service — Free