Synthetic Data
for Software Vendors

Discover how software vendors accelerate development, testing, and innovation with safe, production-like synthetic data.

Health Plus Ai
KPN
Philips
Nederlandse Spoorwegen
Cedars Sinai
New compliance
SAS
Universiteit Leiden
Lifelines
Centraal Bureau voor de Statistiek
Euris Group
KVK
Leiden University Medical Center
UMCG

The role of data in software

Innovation thrives on data. But for software providers, data access is a bottleneck.

Innovation thrives on data, but when it comes to developing software, data access is a bottleneck. Development teams are under pressure to deliver new features faster, improve product stability, and deliver personalized experiences, but privacy regulations, slow approvals, and incomplete datasets hold them back.

Testing with real data isn’t allowed, and when it is, it’s risky. Whereas masked or fabricated datasets often break workflows, delay releases, and increase the likelihood of bugs in production, leaving teams struggling to meet deadlines and quality standards.

Person struggling with data access

Why Traditional Test Data Management Holds Software Vendors Back

Blocked from using real production data

Problem:
Privacy regulations prevent dev teams from accessing and using real customer data in non-production environments, slowing testing, limiting realism, and increasing privacy risk.

 

Solution:
With Syntho, generate privacy-safe synthetic datasets that look and behave like production data, without containing any sensitive information.

 

Value Outcomes:

  • Shorten test data provisioning time
  • Test earlier in the development cycle wtih fewer data access delays
  • Maintain full data utility without risking exposure
Broken data relationships cause test failures

Problem:
Inconsistencies between datasets break referential integrity, leading to failed tests, inaccurate results, and unstable environments.

 

Solution:
Syntho preserves relationships between tables, databases, and systems, ensuring that test data behaves consistently across all environments.

 

Value Outcomes:

  • Consistent, production-like environments that prevent mismatches and data errors during development and testing

  • Improved test accuracy by ensuring data remains reliable and complete across systems

  • Reduced time spent fixing broken test setups

Test data doesn’t reflect production reality

Problem:
Masked or manually created test data fails to match real business rules, workflows, and complexity, leaving critical coverage gaps.


Solution: Generate synthetic datasets that accurately reflect real-world workflows and logic, so tests are realistic and complete.


Value Outcomes:

  • Detect more defects before release
  • Improve feature validation accuracy
  • Reduce costly post-release fixes
Slow and manual test data creation delays releases

Problem:
Teams spend hours to weeks preparing and masking data, taking time away from building and shipping features.

 

Solution:
Quickly generate privacy-safe, production-like test data with Syntho on-demand.

 

Value Outcomes:

  • Shorter test cycles and faster release timelines

  • Free up engineering resources for high-value work

  • Data available on-demand

Can’t test rare or future scenarios

Problem:
Missing edge cases, negative flows, or hypothetical scenarios leave systems unprepared for real-world incidents.

 

Solution:
Use Syntho’s rule-based generation to create rare, future, or extreme scenarios for comprehensive system testing.

 

Value Outcomes:

  • Improve resilience and system stability

  • Validate “what-if” scenarios before they happen

  • Ensure features work across all possible conditions

Critical bugs slip through before releases

Problem:
Without realistic and comprehensive test data, critical bugs go undetected until after deployment, leading to expensive fixes.

 

Solution:
Generate complete, production-like datasets that include edge cases and complex logic, ensuring defects are caught earlier.

 

Value Outcomes:

  • Reduce post-release bugs

  • Protect brand reputation and customer trust

  • Lower long-term maintenance costs

See the Top Use Cases for Software Vendors

Check out how software vendors can use synthetic data within their organizations

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Accelerate innovation in your software development lifecycle

01
Product & Feature Development

Build features faster with safe, production-like data. With Syntho, teams can:

 

  • Accelerate release cycles by removing delays from data access and provisioning
  • Maintain consistent datasets across development, testing, and staging environments
  • Enable more data-driven use cases without being blocked by privacy reviews
  • Test new features early with realistic, production-like data before systems go live
02
Test Data Management & Demo Data

Reduce data delays and privacy risks from your development and sales cycles. With Syntho, teams can:

 

  • Reduce production bugs by testing with high-fidelity, representative datasets
  • Quickly generate privacy-safe data to speed up test execution
  • Simulate rare and edge cases to expand test coverage and reliability
  • Create safe, realistic demo environments for sales, training, and onboarding
03
Data Sharing & AI Modeling

Unlock secure collaboration and advanced AI modeling with fewer privacy headaches. With Syntho, teams can:

 

  • Share datasets safely across internal teams, regions, and external partners
  • Train AI/ML models on diverse, production-like synthetic data
  • Experiment freely with analytics and prototypes without exposing sensitive information

Relevant features applied to Software Vendors

Enhance data-privacy

Data Masking

Automatically detect and protect sensitive data while keeping it usable for development and testing.

With Syntho’s data masking capabilities, you can transform real customer data into privacy-safe alternatives that preserve structure and relationships, CI/CD pipelines, and internal QA with fewer risk.

Learn more
Remove privacy risks from your data

Automatically identify sensitive values

PII Scanner

Identify direct identifiers (such as PII and PHI)  automatically with our AI-powered PII Scanner 

This means you can quickly spot PII/PHI across databases and text fields with fewer and shorter manual checks. 

Learn more
Automatically identify sensitive values

Replace sensitive values with representative values

Synthetic Mock Values

Substitute sensitive PII, PHI, and other identifiers with reprenentative mock data.

Our platform automatically suggests the correct mocker for each PII entity, saving time and reducing manual work.

Learn more
Replace sensitive values with representative values

Maintain data consistency across environments

Consistent Mapping & Referential Integrity

Ensure that relationships between tables, databases, and systems remain intact in your synthetic datasets. Syntho preserves foreign keys and data linkages, enabling reliable end-to-end testing, stable automation pipelines, and accurate multi-table analytics without mismatches or broken dependencies.

Learn more
consistent mapping with blue background

Reflect real-world scenarios

Rule-Based Synthetic Data

Apply business rules to generate data that reflects real-world workflows, user behavior, and edge cases specific to your application. 

Ensure your test datasets are not only statistically accurate but contextually meaningful for validating complex product logic, integrations, and risk scenarios.

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Reflect real-world scenarios

Download the Syntho Guide for Software Vendors

Explore the role of synthetic data in software

Download

How Syntho works for Software Vendors

Learn how Syntho simplifies secure and privacy-safe synthetic data generation in just a few steps

How Syntho works in FinTech
01
Deploy in your environment

Run Syntho entirely within your trusted environment, whether on-premise or in a private cloud, so sensitive customer or application data never leaves your control.

02
Connect to your database

Easily integrate with your application databases, data warehouses, or development environments using Syntho’s out-of-the-box connectors.

03
Generate your data

Once connected, you can choose to mask values, generate new synthetic records, or transform sensitive data automatically. Syntho preserves time patterns and statistical relationships, making it ideal for testing features, running QA, training AI models, or powering demo environments.

04
Share/Use the protected data

Once generated, your synthetic data can be safely used across development, testing, staging, partner sandboxes, demos, and analytics without triggering privacy reviews. Share them internally or externally with confidence and agility.

Case studies

Explore real-world success stories from our clients.

Synthetic data for the National Statistical Office, Statistics Netherlands (CBS)

Synthetic data for the National Statistical Office, Statistics Netherlands (CBS)

Empower CBS’s statistical excellence with secure synthetic data solutions and learn how they are shaping the future of statistical

Synthetic test and development data with a leading EMR and healthcare solutions

Synthetic test and development data with a leading EMR and healthcare solutions

Enhance your EMR and healthcare solutions with Syntho’s synthetic test and development data, enhancing privacy compliance and operational

Synthetic data for academic research at the Erasmus University

Synthetic data for academic research at the Erasmus University

Revolutionizing academic research at Erasmus University with synthetic data. Discover how it enhances data accessibility and privacy in

Synthetic data for the The Netherlands Chamber of Commerce (KVK)

Synthetic data for the The Netherlands Chamber of Commerce (KVK)

Discover how synthetic data for a Dutch governmental organization enables fast, secure, and actionable initiatives.

Synthetic data for advanced analytics and testing with a leading international bank

Synthetic data for advanced analytics and testing with a leading international bank

Unlock the potential of synthetic data for AI/ML modeling, advanced analytics, and testing with a renowned International Dutch Bank.

Synthetic test and development data with a leading Dutch insurance company

Synthetic test and development data with a leading Dutch insurance company

Explore the innovative world of synthetic test and development data in collaboration with a prominent Dutch insurance company.

Synthetic data for software development and testing with a leading Dutch Bank

Synthetic data for software development and testing with a leading Dutch Bank

Check out how synthetic data for software development and testing can help solving privacy issues of a leading Dutch Bank.

Synthetic patient EHR data for advanced analytics with Erasmus MC

Synthetic patient EHR data for advanced analytics with Erasmus MC

Discover how Erasmus MC utilizes synthetic patient EHR data to advance analytics and testing, ensuring patient privacy while fostering

Synthetic data generation for data sharing with Lifelines

Synthetic data generation for data sharing with Lifelines

Discover how Lifelines partnered with Syntho to generate synthetic biobank data, enhancing data accessibility for researchers while

Synthetic healthcare data for a leading US hospital

Synthetic healthcare data for a leading US hospital

Discover how a leading U.S. hospital leverages synthetic data to enhance patient privacy, advance medical research, and improve clinical

Case studies

Why Syntho?

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Accelerate release cycles with privacy-safe test data

Cover edge cases and rare scenarios for better product quality

Enable secure data sharing across teams and environments

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