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Open Source Synthetic Data Orchestration

A developer-first way to create anonymized or synthetic data and sync it across all environments for testing and machine learning

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Protect Your Sensitive Data, Build Faster with Neosync
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Unblock local development
Shift left and give developers the ability to self-serve de-identified and synthetic data locally whenever they need it without having to worry about sensitive data privacy or security.
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Fix broken staging environments
Catch production bugs and ship faster when you hydrate your staging and QA environments with production-like data that is safe and fast to generate.
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Keep environments up to date
Speed up your dev and test cycles. Make sure your environments stay in sync with the latest de-identified and synthetic data that you can refresh whenever you need to.
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Frictionless security, privacy and compliance
Easily and quickly abide by laws like HIPAA, GDPR, and DPDP with de-identified and synthetic data that structurally and statistically looks just like your production data.
Get Up and Running in Minutes
Whether you want to run Neosync locally, on VMs or in Kubernetes, Neosync is easy to deploy using Docker or Helm.
1
Deploy
Start Neosync locally using Tilt or Docker compose. When you're ready, deploy Neosync using a Helm Chart or Docker Compose.
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2
Connect
Connect your source and destinations. Neosync supports Postgres, Mysql, S3 and we're always building more integrations.
3
Configure
Configure your schemas, tables and columns with transformers that de-identify your data or generate synthetic data. Neosync automatically handles all relational integrity.
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Sync
Sync data across systems or generate synthetic data from scratch and send it a downstream system.
The Most Flexible Way to Transform Your Data
Transformers anonymize existing data or generate new synthetic data. Choose from 35+ pre-built Transformers or write your own transformer in code.
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Built for Engineering Teams
From Local, to Stage to CI, Neosync has APIs, SDKs and a CLI to fit into every workflow.
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Get started with synthetic data at scale
Join our Community
Have questions about Neosync? Come chat with us on Discord!
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