Realistic data for testing, training and development – without privacy risk.
You need realistic data for software testing, training or new systems – but can't use real data for privacy reasons? Or there simply isn't enough test data for your use cases? We generate synthetic data that mirrors your real-world structures and patterns – tabular or document-based. We combine rule-based methods with AI-powered generation, depending on your requirements. As a custom project or with optional self-service access for your team. The price depends on scope, variance and edge cases and is always communicated transparently upfront.
Realistic test data without privacy risk – tailored to your use case
Whether for system testing, employee training or developing new applications – our synthetic data mirrors your real-world structures without putting personal information at risk.
What You Get
Synthetic datasets that mirror your real data structures and patterns
Coverage of standard cases and targeted edge cases
Delivery in your preferred format (CSV, JSON, SQL, PDF, etc.)
Optional: self-service access for independent data generation
Documentation of generation logic and quality checks
How It Works
4 How It Works
01
Requirements Analysis
We understand your data structures, use cases and specific requirements for variance and edge cases.
02
Schema & Rule Design
We define schemas, distributions and rules – combined with AI models for complex patterns.
03
Generation & Validation
We generate the data and validate it for realism, consistency and coverage of your test scenarios.
04
Delivery & Optional Self-Service
You receive the data in your preferred format. Optionally, we set up self-service access so your team can generate additional data independently.
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