Synthetic Data & Augmentation Service

Generate synthetic data to fill gaps, protect privacy, or train AI when real data is scarce or sensitive. Ideal for innovators who need data but don’t want the compliance headache.

More Data Without More Drama

What do you do when the data you need… doesn’t exist? Or worse—when the data you have is too sensitive, too biased, or too limited?

Inventive’s Synthetic Data & Augmentation Service generates high-fidelity, AI-ready data to fuel training, testing, and optimization—without the privacy headaches or long collection cycles.

We use GANs, SMOTE, and generative AI (like GPT-4) to create structured tables, text, images, or transactions that mimic the real world—without copying it.

Need to model rare fraud cases? We’ll synthesize them. Need 50,000 labeled chat transcripts? We’ve got you. Want to augment for fairness or regulatory safety? Done.

Why Inventive? We don’t just generate data—we validate it. Our data scientists ensure synthetic datasets align with real-world distributions, model goals, and regulatory compliance. It's not fake data—it’s future-proof fuel.

The cost of waiting? Biased models, privacy risks, and missed opportunities. Your competitors are creating tomorrow’s data—today.

The data was sensitive. The solution was synthetic.

We needed fraud data—but couldn’t risk exposing real customers. Synthetic augmentation gave us both privacy and precision.

Chief Data Officer, Fintech Startup

More Data Without More Drama

  • You're missing data for rare but critical edge cases.
  • Your lawyers just said "no" to that training set.
  • You need 10x more data, but 0x more privacy risk.
Up to 20%

Model Lift

After synthetic data augmentation

Balanced data = smarter predictions, less overfitting.

$10K–$50K

Per Engagement

Custom projects + recurring dataset refreshes

Low-input, high-output services that scale with demand.

9/10

AI Synergy Score

Synthetic data is model fuel when real data falls short

Great for privacy, rare cases, and scaling fast.

More Data Without More Drama

Criteria Real-Only, Risky & Limited Manual Augmentation, Little Strategy This Tier: Smart, Scalable Synthetic Data
Dataset Diversity Skewed toward frequent behaviors Slight improvement, still imbalanced Balanced, class-augmented, and privacy-respectful
Privacy Risks High—PII or regulated content Moderate masking, still fragile Fully synthetic = no real users = no breaches
Model Performance Biased, underfit, or overfit Some lift, still unreliable Improved accuracy, especially on edge cases