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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 sales
AK
ML
SR
DT
JP
500+ data teams already using Hadarac
10M+ records generated
<2s avg generation

Trusted 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

across all datasets

99.9%
Uptime

production SLA

< 2s
Generation time

avg. per dataset

3
Privacy modes

Generate · Redact · Extend

Everything you need

The full synthetic data
lifecycle, in one place

From first generation to production-ready dataset — Hadarac handles every step without touching real data.

Generate
Generate 500 e-commerce orders with realistic PII…
Generate
order_id
customer
amount
status
#10042
Sarah L.
$84.99
shipped
#10043
James W.
$212.00
pending
#10044
Mei C.
$37.50
delivered

Generate from natural language

Describe your schema in plain English. Hadarac builds a complete, realistic dataset in seconds — no templates, no sample data, no SQL.

Refine
Row 12 — excellent match
Row 7 — too generic
Row 31 — good, minor fix
Regenerating 2 rows…

Rate rows, get better data

Score each row 1–5 stars. Hadarac learns your feedback and regenerates improved rows instantly.

Extend
Your CSV → + new columns
name
email
city
+ income ✦
Alice B.
alice@…
London
$72,400
Tom K.
tom@…
Berlin
$58,900
Priya S.
priya@…
NYC
$91,200

Add columns to existing data

Upload a CSV or Parquet and enrich it with new synthetic columns — without touching your real values.

Redact
emailjohn.smith@acme.com7f2d@synth.data
phone44 7911 123456+44 7000 000001
postcodeNW1 4AB, LondonSW1 9XX, London

Replace PII with realistic synthetics

Swap real names, emails, phone numbers, and addresses with indistinguishable synthetic alternatives. Compliance-ready output — GDPR, CCPA, HIPAA.

Export

Works with your stack

Download CSV, Parquet, or JSON. Drop it straight into pandas, dbt, Snowflake, or any SQL database.

.csv
.parquet
.json
pandasdbtSnowflakeBigQuerySparkPostgreSQL
Generate

Describe your dataset. Get it instantly.

Write a plain-English description of what you need — columns, domain, volume, edge cases. Hadarac generates a complete, realistic dataset in under two seconds. No schema files. No sample data. No SQL.

Start generating free →
hadarac.com/generate
Prompt
Generate 200 realistic e-commerce transactions for a UK fashion retailer. Include order_id, customer_name, email, product, quantity, price_gbp, and status.
200 rows·7 columns·CSV · Parquet
Output200 rows generated
order_idnameemailproductqtypricestatus
#UK-8821Isla T.isla@…Linen blazer1£89.99shipped
#UK-8822Marcus P.m.patel@…Cord trousers2£112.00processing
#UK-8823Fiona H.fionahm@…Silk scarf1£34.50delivered
#UK-8824Aiden R.aiden@…Wool coat1£249.00shipped
Redact

Replace PII before it ever leaves your stack.

Upload any CSV containing real customer data. Hadarac 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 →
hadarac.com/redact
Input file

customers_prod.csv

1,204 rows · 9 columns · 84 KB

PII detected
Before → After
full_nameJonathan Ashworth-ClarkeMarcus Pemberton
emailj.ashworth@clarkeltd.co.ukm.pemberton@synth.data
phone+44 7700 900461+44 7000 000127
postcodeEC1A 1BBSW1A 9ZZ
dob1987-03-141985-07-22
1,204 / 1,204 rows redacted
Extend

Add columns to any dataset without starting over.

Have a dataset but need more signal? Upload your CSV or Parquet and tell Hadarac 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 →
hadarac.com/extend
Existing columns
user_idnamecityagesignup_date
Add new columns
annual_income, job_title, credit_score
Result+3 columns added
namecityageincome ✦job_title ✦credit ✦
Alice B.London29£54,200Product Mgr761
Tom K.Berlin34€71,800ML Engineer810
Priya S.NYC27$83,500Data Analyst688
Sam W.Sydney42A$92,000Sr Dev742

Try it live

No account needed. 10 rows, instant results.

Schema:order_idproduct_namecategoryquantitypricecountrystatus· 10 rows

Ready to generate

order_id · product_name · category · quantity · price · country · status

API-first by design

Generate datasets
programmatically.

Integrate Hadarac 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
Read the docs
import (hadarac)
 
# Authenticate with your API key
client = (hadarac).Client(
api_key="uc_live_sk_••••••••••••••••"
)
 
# Generate a dataset from a plain-English prompt
dataset = client.generate(
prompt="500 UK e-commerce transactions, \n"
"fashion retailer, realistic PII",
rows=500,
format="parquet",
privacy_mode="synthetic"
)
 
# Use it directly with pandas
import pandas as pd
df = pd.read_parquet(dataset.path)
print(df.head(3))
API status: operational
View full API reference →
$pip install hadarac

How it works

From description
to dataset in minutes

No data science background required. If you can describe your data in plain English, Hadarac can generate it.

01

Describe your data

Define your column headers and write a plain English description of what you need. Tell Hadarac about the context, industry, or edge cases you want covered.

Supports any domain — finance, healthcare, e-commerce, logistics, SaaS, and more.

02

Generate & refine

Hadarac 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.

03

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.

Start generating data in 30 seconds

Free forever · No credit card · 15 credits/month

Get started free

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 Hadarac 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. Hadarac 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. Hadarac'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

Trusted by 50+ data teams worldwide

MA
Meridian AI
FA
Forge Analytics
AL
Axiom Labs
TC
TechCraft
DF
DataFlow
NB
NovaBridge

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

FAQ

Common questions

Synthetic data is artificially generated data that mirrors the statistical properties and structure of real-world data — without containing any actual personal information. It's safe to share, test with, and train models on.

Yes. Because no real records are involved, synthetic data eliminates PII exposure, data breach risk, and most compliance concerns. It's commonly used by teams subject to GDPR, HIPAA, and SOC 2 requirements.

Free accounts can generate up to 100 rows per dataset (15 datasets/month). Team plans support up to 1,000 rows per generation with 100 monthly credits. Enterprise plans have no limits.

The Developer plan is free forever (15 credits/month). The Team plan is $295/month for 100 credits, 10 concurrent jobs, and API access. Enterprise pricing is custom — contact sales for a quote.

Yes. Hadarac doesn't store, process, or transmit any real personal data. Generated datasets contain only synthetic values. We also offer data retention controls and a DPA for enterprise customers.

Yes. Every feature available in the dashboard is also accessible via our REST API. Generate API keys in Settings, and use our Python SDK or curl to integrate synthetic data into your CI/CD pipelines.

CSV, JSON, JSONL, Parquet, Excel (.xlsx), and SQL INSERT statements. You can also open results directly in Google Sheets or copy as a TypeScript interface.

Free users can email hello@hadarac.com. Team plans include 1-business-day response SLA. Enterprise plans get 24/7 dedicated support, a Slack channel, and a named success engineer.

Still have questions? hello@hadarac.com

Get started today

Stop waiting for data.
Generate it.

Join the teams using Hadarac 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