Synthetic Data Generation

Get the insights you need—without exposing sensitive information. Unlock analytics, AI, and sharing with privacy-safe synthetic datasets.

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Why Synthetic Data?

When real data is too sensitive, limited, or unbalanced, synthetic data lets you analyze, develop, and share—without risk. We create high-quality datasets that mirror the structure and insights of your real data, but protect privacy and enable collaboration.

Do more with your data—while meeting privacy, legal, and ethical standards.

Where Synthetic Data Delivers Value

Privacy-Preserving Sharing

Share data with partners or teams—without exposing sensitive or regulated information.

Example: A health network generates a synthetic dataset to collaborate with researchers, avoiding HIPAA compliance risks.

Machine Learning & AI Augmentation

Balance rare events, boost model accuracy, or test algorithms when real data is scarce.

Example: A fintech company creates balanced synthetic fraud cases, improving their AI’s ability to spot rare but costly patterns.

Scenario Testing & Prototyping

Test new products, analytics pipelines, or business cases—without using live customer data.

Example: A retailer develops and tests analytics dashboards on synthetic sales data, keeping customer info private.

Benchmarking & Safe Evaluation

Compare tools, vendors, or new workflows—using realistic synthetic benchmarks instead of sensitive business data.

Example: An insurer tests a new claims process on synthetic data, identifying issues without exposing private customer records.

Our Synthetic Data Process

  1. Free Discovery Call: Tell us your goals and data challenges. We’ll share use cases, sample outputs, and transparent pricing—no commitment.
  2. Data Health Check: We review your reference data and privacy needs, checking for readiness and any blockers.
  3. Design & Generation: We choose the best synthesis method (AI, copulas, permutations, etc.), generate synthetic data, and validate quality and privacy.
  4. Validation & Handover: You get data, code, validation reports, and clear documentation—plus support contacts for questions or refreshes.
  5. Optional Ongoing Support: Need new datasets or updates? We offer regular refreshes and privacy reviews as your needs change.

What You Need to Get Started

  • Reference data or clear description of needed dataset
  • Clear business or privacy goal (sharing, ML, prototyping, etc.)
  • Sample size of at least 500 records (if possible)
  • Willingness to sign a mutual NDA (we protect your data and results)

Not sure if your use case fits? Most organizations can benefit from synthetic data—book a free consult to see how it works for you.

Starter Pricing

  • Pre-consult & Discovery: Free
  • Typical synthetic data project: $2,200 – $4,200

Contact us for a tailored quote—every dataset is built for your privacy, business, and compliance needs.