Faster & Easier Synthetic Data at Scale: The New Syntho Platform

Working with data is rarely straightforward. Large databases with hundreds of tables, complex relationships, and strict governance requirements make it difficult to move fast. For teams using synthetic data, this often means spending more time configuring environments than generating insights.

At Syntho, our mission is to remove those barriers. We believe synthetic data should be not only powerful but also practical and scalable. That’s why we’ve introduced a major update to our platform: a new user interface and a set of features designed to make configuration easier, speed up workflows, and scale synthetic data generation across entire organizations.

The new Syntho Platform helps teams configure, generate, and scale privacy-preserving data up to 50× faster. Here’s what’s new.

TL;DR:

The new Syntho Platform introduces a smarter UI, automated configuration, and faster workflows, helping teams configure, generate, and scale privacy-preserving synthetic data up to 50× faster. With new features like Rule-Based Synthetic Data, Virtual Tables, Workspace Modes, and the Main Hub, teams can build and manage synthetic datasets more efficiently across their entire data landscape.

Key highlights:

• Rule-Based Synthetic Data: Create any edge case or scenarios using all 150+ mockers combined with Rule-Based Synthetic Data
• Virtual Tables: Create custom datasets without extra storage
• Workspace Modes: Automate configuration across databases in one step
• Main Hub: Apply generator settings in bulk for up to 20,000+ columns
• New UI: Streamlined design for faster setup and collaboration

Rule-Based Synthetic Data

Design complex logic with realistic, privacy-preserving outputs

You can now use all of Syntho’s 150+ mock generators directly in your calculated column formulas, with the ability to fine-tune every configuration parameter. 

Until now, only a subset of mock generators was supported within calculated columns, and you were limited to their default configurations. That meant less flexibility in creating realistic, tailored mock data within your calculated fields. With this update, those limitations are gone. 

You can now:

• Seamlessly integrate any mock generator into a calculated column formula. 
• Adjust configuration parameters for each generator, giving you full control over the output. For example, you can change the locale per mocker or enable as unique. 
• Reuse generated values across your formula by referencing the same generator multiple times. 

For example, one of our clients needed a secure way to anonymize their SSN numbers so they couldn’t be traceable back to the original person. They required the SSN to always start with 999, followed by random digits, while applying transformation (like +1, +2 shifts) on certain digits for added randomness.   

This resulted in fully anonymized SSNs that preserve realistic formatting, while remaining consistent across different databases, and removing the risk of backward traceability. 

Impact: 

• More flexibility: Combine any mock generator with your business logic. 
• Greater realism and broader coverage of edge cases: Configure parameters for more accurate, context-specific mock data. 
• Consistency across databases: Ensures anonymized or calculated columns behave the same in every environment 

This enhancement gives you the freedom to design your formulas exactly the way you need them, combining complex logic with powerful mock data generation, all in one place. 

Learn more: CRule-Based Synthetic Data alculated Columns 

Virtual Tables: Create custom datasets without extra storage 

Generate the exact data you need without moving it

Until now, the platform allowed users to load and synthesize database tables. With this release, you can also work with database views. Views make it possible to prepare and synthesize custom datasets tailored to specific use cases. This is especially valuable in AI and analytics projects, where building a single “feature table” is often the key to achieving high-quality results.

A key advantage is that views do not require additional storage. Teams can prepare the datasets they need without duplicating or moving data.

Impact:

• Faster data preparation: Data scientists can generate feature tables directly, reducing the need for complex data engineering
• Targeted datasets: Analytics teams can create focused datasets for specific questions
• Cost efficiency: Organizations avoid additional storage costs while gaining more flexibility

Explore our interactive demo

Workspace Modes: Automate Synthetic Data configuration

One setup for your whole workspace 

Configuring large databases can be time-consuming. Traditionally, users needed to adjust the generator settings table by table, leading to repetitive work and slower project setup.

With Workspace Modes, generator settings can now be applied across the entire workspace in one step. The platform also provides smart suggestions based on the use case you define. This reduces the number of manual adjustments and ensures consistency across projects.

Impact:

• Up to 90% fewer manual configurations 
• Reduced configuration errors through consistent settings.
• Teams can spend less time clicking and more time generating data.

Learn more: Workspace Modes

Main Hub (Bulk Apply): Configure hundreds of tables in one step

Scale configurations across databases in seconds

Setting up synthetic data across thousands of columns no longer needs to be a slow, manual process. With the new Main Hub, you can run large-scale actions in just a few clicks cutting setup time dramatically to

• Run a PII scan across every column in your database at once
• Apply AI-recommended workspace mode generation settings across all columns in a single action, instead of opening each column’s configuration panel individually
• Manually configure generators in bulk to adjust up to 50 columns in one go instead of one-by-one
• Custom generator configurations for specific requirements.

This functionality ensures that large environments can be configured quickly and consistently, without compromising security or flexibility.

Impact:

• Up to 50× faster configuration with bulk generator application
• Up to 20,000× faster setup with suggested generators for large databases
• Consistent generator application across all columns with one action

Learn more: Main Hub

Streamlined workflows, faster results

A redesigned UI for speed, clarity, and collaboration

This update is more than a visual refresh. The new UI reduces the number of steps needed to configure masking or synthesis, helping teams move from setup to results faster.

We rethought the entire interface to make complex tasks simpler, reduce friction across workflows, and ensure that anyone, whether technical or non-technical, can generate synthetic data with confidence. By simplifying navigation, surfacing key actions, and guiding users through configuration, the new UI eliminates unnecessary complexity without compromising control.

Impact:

• Faster project setup: Projects can now be configured more quickly, which helps teams achieve results faster.
• Quicker onboarding: New users can onboard quickly thanks to intuitive workflows that require less training.
• Cross-team adoption: Both technical and non-technical teams can work productively, leading to broader adoption across the organization.
• Fewer errors: Streamlined processes reduce human error, which strengthens both data quality and privacy standards.

The result is not just a better-looking platform, but a user experience designed to make synthetic data practical, scalable, and accessible across entire organizations. 

Why Usability Matters in Synthetic Data

Synthetic data adoption is growing rapidly, but many organizations still face challenges in operationalizing it. Complex configuration, slow setup, and poor user experiences can hold back projects that otherwise have strong business cases.

By addressing these usability challenges, Syntho enables teams to focus on what synthetic data is meant to deliver: faster innovation, stronger compliance, and more accessible data for AI, analytics, and testing.

Looking Ahead

This release marks a major step forward in making synthetic data both powerful and practical. By combining improved scalability with a streamlined interface, Syntho is helping organizations unlock more value from their data while reducing operational friction.

These features are live on the platform today. Log in to explore the new UI and experience the updates yourself.

Not yet a customer? Book a demo to see how Syntho can help your organization generate high-quality synthetic data at scale.