Realistic synthetic person data.
One API call.
65 attributes per record. Demographics, health, financial, behavioral. Calibrated against NHANES, ACS, and CDC. No source dataset required. No signup to try.
curl -s -X POST https://api.simpleidgen.com/v1/mock/person \
-H 'Content-Type: application/json' \
-d '{"count": 10}'What you get
Not random fillers
Every attribute is drawn from published US reference distributions. BMI correlates with height and weight. ZIP codes match states. Diabetes prevalence rises with age. Formally tested with KS and chi-squared against NHANES, ACS, CDC, and KFF.
No source dataset required
Most synthetic data tools need your real data first. This one doesn't. Built entirely from public reference data. No real PII ever enters the system.
Deterministic by seed
Same seed, same data. Every time. Pin your test fixtures, reproduce bugs, version your test datasets. Different seed, different people.
Bulk export to S3
Need millions of rows? The async endpoint streams up to 10M records as JSONL to S3. Download link active for 90 days.
Built for
Startups building health-tech
Need realistic patient records for your MVP?
Demo to investors with data that looks real, not "John Doe, age 30".
Students & researchers
Teaching or studying healthcare analytics? Get a 10K-row dataset in 5 seconds instead of fighting IRB for 6 months.
QA & test engineers
Populate staging environments with realistic data. Deterministic seeds make test fixtures reproducible across CI runs.
Ready?