Synthesized closed a $20M Series A to expand synthetic data generation and AI-driven testing for regulated enterprises. The round is another signal that “test data infrastructure” is becoming a budget line item as privacy and compliance constraints tighten.
Synthesized closes $20M Series A to expand AI-driven testing in regulated industries
Synthesized, a London and New York-based startup focused on generating synthetic data for software testing, raised $20 million in Series A financing. The round was led by Redalpine Venture Partners and took place in September 2025.
Other investors named in the round include IQ Capital, Mercia Ventures, UBS, Seedcamp, and Deutsche Bank. Founded in 2020 by Nicolai Baldin, the company positions its product around creating realistic synthetic test data and testing environments to help enterprises find bugs and vulnerabilities without relying on sensitive production datasets. The company cites Deutsche Bank as an early adopter, and says the funding will be used to expand its engineering team, refine its AI-driven testing capabilities, and grow its footprint across North America and Europe—particularly for customers operating under heavy regulatory constraints such as financial services.
- Less production data in QA means less risk. Shifting test pipelines away from real customer records can reduce exposure under regimes like GDPR and HIPAA, especially where test environments tend to be loosely governed.
- Data teams get leverage when test data becomes “self-serve.” If synthetic data generation is reliable, it can shrink the queue of manual data extracts, masking requests, and one-off approvals that slow release cycles.
- Security and compliance teams will push for proof, not promises. Expect procurement questions around fidelity, constraint handling, and whether “synthetic” outputs can still leak information about underlying sources—plus requirements for audit trails and policy enforcement.