Generate synthetic data
at any scale
Create realistic, privacy-safe datasets from plain English. Test AI models, validate data pipelines, and ship products faster — without ever touching sensitive data.
Talk to salesTrusted by teams building with
- Python
- pandas
- dbt
- Snowflake
- BigQuery
- Apache Spark
- PostgreSQL
- Parquet
- Python
- pandas
- dbt
- Snowflake
- BigQuery
- Apache Spark
- PostgreSQL
- Parquet
Trusted by data teams at
- Luminary Data
- Axiom Labs
- Forge Analytics
- Meridian AI
- Paragon Systems
- Nexus ML
- 10M+
- Records generated
- 99.9%
- Uptime
- < 2s
- Generation time
- 3
- Privacy modes
across all datasets
production SLA
avg. per dataset
Generate · Redact · Extend
Everything you need
The full synthetic data
lifecycle, in one place
From first generation to production-ready dataset — Unicourn handles every step without touching real data.
Generate from natural language
Describe your schema in plain English. Unicourn builds a complete, realistic dataset in seconds — no templates, no sample data, no SQL.
Rate rows, get better data
Score each row 1–5 stars. Unicourn learns your feedback and regenerates improved rows instantly.
Add columns to existing data
Upload a CSV or Parquet and enrich it with new synthetic columns — without touching your real values.
Replace PII with realistic synthetics
Swap real names, emails, phone numbers, and addresses with indistinguishable synthetic alternatives. Compliance-ready output — GDPR, CCPA, HIPAA.
Works with your stack
Download CSV, Parquet, or JSON. Drop it straight into pandas, dbt, Snowflake, or any SQL database.
Describe your dataset. Get it instantly.
Write a plain-English description of what you need — columns, domain, volume, edge cases. Unicourn generates a complete, realistic dataset in under two seconds. No schema files. No sample data. No SQL.
Start generating free →Replace PII before it ever leaves your stack.
Upload any CSV containing real customer data. Unicourn detects and replaces names, emails, phone numbers, postcodes, and dates of birth with statistically realistic synthetic equivalents — preserving format, distribution, and referential integrity.
See how redaction works →customers_prod.csv
1,204 rows · 9 columns · 84 KB
Add columns to any dataset without starting over.
Have a dataset but need more signal? Upload your CSV or Parquet and tell Unicourn which columns to add. It infers relationships from existing data and generates new columns that are statistically consistent with what you already have.
Try Extend →Generate datasets
programmatically.
Integrate Unicourn into any pipeline with a single API call. Trigger dataset generation from CI/CD, seed test databases automatically, or embed synthetic data directly into your data platform.
- Python SDK + REST API
- Streaming responses for large datasets
- Webhook support for async generation
- OpenAPI spec available
import unicourn# Authenticate with your API keyclient = unicourn.Client(api_key="uc_live_sk_••••••••••••••••")# Generate a dataset from a plain-English promptdataset = client.generate(prompt="500 UK e-commerce transactions, \n""fashion retailer, realistic PII",rows=500,format="parquet",privacy_mode="synthetic")# Use it directly with pandasimport pandas as pddf = pd.read_parquet(dataset.path)print(df.head(3))
pip install unicournHow it works
From description
to dataset in minutes
No data science background required. If you can describe your data in plain English, Unicourn can generate it.
Describe your data
Define your column headers and write a plain English description of what you need. Tell Unicourn about the context, industry, or edge cases you want covered.
Supports any domain — finance, healthcare, e-commerce, logistics, SaaS, and more.
Generate & refine
Unicourn generates your dataset instantly using Gemini 2.5 Flash. Rate individual rows to provide feedback — the system learns and improves with each iteration.
Typically 2–3 feedback rounds to reach production quality.
Download & ship
Export as CSV or Parquet with one click. Use your synthetic dataset in testing pipelines, model training, demos, or anywhere real data would create compliance risk.
Works with pandas, Spark, dbt, Snowflake, BigQuery, and any SQL database.
What teams are saying
Loved by data teams
"We used to spend two sprints just anonymising prod data before handing it to QA. Now I run a Unicourn generate call in our CI pipeline and the test database seeds itself. We shipped our last three features two weeks early."
Sarah Chen
Senior Data Engineer · Meridian AI
"Our model needed training data for edge-case fraud patterns that almost never appear in real transactions. Unicourn let us describe the patterns in plain English and generate 50,000 synthetic examples in minutes. The precision improvement was immediately measurable."
James Okafor
ML Platform Lead · Forge Analytics
"GDPR was a blocker every time we wanted to share a dataset across teams. Unicourn's redact mode replaced every piece of PII while keeping the statistical shape of the data intact. Legal signed off in a day — that's never happened before."
Priya Mehta
Head of Data · Axiom Labs
Enterprise-grade security
SOC 2 Type II
In progress
GDPR Ready
EU compliant
No data retention
Zero-log processing
End-to-end encryption
TLS 1.3 + AES-256
EU / US hosting
Choose your region
Get started today
Stop waiting for data.
Generate it.
Join the teams using Unicourn to build faster, ship more confidently, and eliminate data compliance risk for good.
No credit card required · Free tier available · Up and running in 2 minutes