Realistic patients. No real data.
Your staging database has 14 test patients. They were all created in 2019. Flock generates synthetic patient populations grounded in real public health data — clinically coherent, relationally consistent, ready to load.
Your go-live is in three weeks. Compliance says you can’t copy production data to staging without a data use agreement, a risk assessment, and sign-off from two committees. The committee meets monthly.
Meanwhile, your staging environment has 14 test patients. None of them have comorbidities. None have overlapping encounters. None will trigger the edge case that breaks your schema migration on go-live day.
You need thousands of patients that behave like real patients — without touching real data.
Diabetic patients get diabetic medications and diabetic labs. Pediatric patients have parents and insurance. Every generated record is internally consistent — because your application expects data that makes clinical sense, not random values.
Flock uses published prevalence data to match real-world disease distributions for your specified geography. Mississippi staging environments look like Mississippi — not a national average that accurately describes nowhere.
SQL INSERT statements for your database. CSV for your ETL pipeline. HL7 messages for your Mirth test channel. FHIR bundles for your API team. One population, every format.
Six weeks of legal review. Or one command.
Be first to know when Flock ships.
Flock is in development. Post — the free CLI for healthcare test message generation — is available now.
Built for the people who keep healthcare data moving.