Unlimited Data.
Zero Privacy Risk.
Generate high-fidelity synthetic data for AI training without exposing sensitive information
Why Synthetic Data?
Real data is expensive, risky, and often unavailable
Limited Real Data
Privacy Regulations
Imbalanced Datasets
High Data Costs
Use Cases
Solve real problems with synthetic data
AI Model Training
Generate unlimited training data for ML models
Testing & QA
Create realistic test data for software validation
Data Augmentation
Expand existing datasets with synthetic variations
Privacy Compliance
Replace real data with synthetic for dev/test
Rare Events
Generate edge cases and anomalies
Data Sharing
Share datasets without exposing sensitive info
Cutting-Edge Technology
State-of-the-art generative AI methods
All Data Types Supported
Generate any type of data you need
Tabular Data
- →Customer records
- →Financial transactions
- →Medical records
Text Data
- →Customer reviews
- →Support tickets
- →Documents
Image Data
- →Medical scans
- →Product photos
- →Faces
Time Series
- →Stock prices
- →IoT sensors
- →Web traffic
Audio Data
- →Voice recordings
- →Music
- →Sound effects
Graph Data
- →Social networks
- →Knowledge graphs
- →Molecules
100% Privacy Guaranteed
Synthetic data contains zero real individuals - mathematically proven
Zero Re-identification Risk
Cannot reverse-engineer real individuals
Differential Privacy
Statistical guarantees of privacy
No PII
Contains no personally identifiable information
High-Fidelity Data
Indistinguishable from real data
Statistical Similarity
Matches real data distribution
Utility Preservation
ML model performance retained
Diversity
Wide coverage of data space
Novelty
New samples, not memorized
Our Process
From real data to synthetic in 3-5 weeks
Compliance Made Easy
Meet all privacy regulations automatically
GDPR
HIPAA
CCPA
SOC 2
Why Choose Synthetic Data?
Unlimited Data
Generate as much as you need
Zero Privacy Risk
No real individuals in data
90% Cost Savings
vs. collecting real data
1000x Faster
Generate in minutes, not months
Industries We Serve
Trusted by leading organizations
Healthcare
Medical records, patient data, clinical trials
Finance
Transaction data, credit histories, fraud patterns
Retail
Customer behavior, purchase histories, inventory
Insurance
Claims data, risk profiles, actuarial modeling
Telecom
Call records, network traffic, customer churn
Manufacturing
Sensor data, defect patterns, quality control
Quality Validation
Every dataset rigorously tested
Statistical Tests
- ✓Distribution matching
- ✓Correlation preservation
- ✓Outlier detection
ML Performance
- ✓Model accuracy on synthetic
- ✓Feature importance
- ✓Generalization
Privacy Tests
- ✓Membership inference
- ✓Attribute disclosure
- ✓Re-identification risk
Domain Experts
- ✓Human review
- ✓Domain validity
- ✓Business logic
Synthetic vs. Real Data
Real Data Challenges
- ✗Privacy risks and regulations
- ✗Expensive to collect and label
- ✗Limited availability
- ✗Imbalanced and biased
- ✗Slow to obtain
Synthetic Data Benefits
- ✓Zero privacy risk
- ✓90% cheaper
- ✓Unlimited quantity
- ✓Balanced on demand
- ✓Generated in minutes
Success Stories
Healthcare AI Startup
Needed 100K patient records but could not access real data due to HIPAA
Generated synthetic patient data preserving medical correlations
Trained ML model with 94% accuracy, zero privacy risk, launched in 3 months
Fintech Company
Imbalanced fraud dataset - only 0.1% fraudulent transactions
Generated synthetic fraud examples to balance training data
Fraud detection accuracy improved from 85% to 96%
Transparent Pricing
Pay once, use forever
Standard
- ✓Up to 100K records
- ✓Quality validation
- ✓Privacy report
- ✓2 months support
Enterprise
- ✓Unlimited records
- ✓Multi-format output
- ✓Dedicated team
- ✓6 months support
Project Timeline
Typical 3-5 week delivery
Client Testimonials
Synthetic data allowed us to train AI without privacy concerns. Game changer for our healthcare product.
We generated 1M synthetic records in 2 weeks. Would have taken 6 months and $500K to collect real data.
Common Questions
Is synthetic data as good as real data?
For most AI applications, yes. Our synthetic data preserves 95%+ of statistical properties and ML utility. Some edge cases may require real data, but for training, testing, and development, synthetic data is often superior due to balance and privacy.
Can synthetic data be traced back to real individuals?
No. Synthetic data is mathematically proven to contain zero real individuals. It is generated from learned distributions, not copied from real records. This is why it is considered non-personal data under GDPR.
What data do you need from us?
We need a sample of your real data (or a schema/description if data is too sensitive). Minimum 1000 records for tabular data, more for complex types. The more data you provide, the higher the quality of synthetic output.
How long does it take?
Typically 3-5 weeks for standard projects. Simple tabular data can be done in 2 weeks, complex multi-modal data may take 6 weeks. Rush projects available for additional fee.
What formats do you deliver?
CSV, JSON, Parquet, SQL databases, or any custom format you need. We also provide quality reports, privacy validation, and generation code if requested.
Can we generate more data later?
Yes! We deliver the trained generative model along with the data. You can generate unlimited additional samples on your own, or we can do it for you as part of support.
Generate Your
Synthetic Dataset
Free consultation to discuss your data needs and privacy requirements