A common challenge in software development is generating test data for development and test environments. Ideally, test data should be as production-like as possible, while ensuring no personally identifiable or sensitive information is exposed. Though this may seem straightforward, test data generation is far from simple. That's why we’re interested in Synthesized — a platform that can mask and subset existing production data or generate statistically relevant synthetic data. It integrates directly into build pipelines and offers privacy masking, providing per-attribute anonymization through irreversible data obfuscation techniques such as hashing, randomization and binning. Synthesized can also generate large volumes of synthetic data for performance testing. While it includes the obligatory GenAI features, its core functionality addresses a real and persistent challenge for development teams, making it worth exploring.
