A trusted standard for synthetic data quality — with zero data access

Evaluate the quality of synthetic data against a trusted standard.
SynData analyzes accuracy, privacy, and utility without accessing your original datasets.

SynData quality evaluation
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Validate synthetic data securely.
Without accessing the original data.

Validate with CUBIG Data Non-Access Technology. Your original data is never exposed, copied, or transferred.

Zero original data access

Validate with CUBIG Data Non-Access Technology. Your original data is never exposed, copied, or transferred.

PIPC-certified

SynData is the only authority that can validate synthetic data compliance under PIPC guidelines — independent, validated, compliant by design.

Validation report within one day

Up to 1 day

Validation report

Receive a detailed validation report within an hour. Includes structure, similarity, and compliance scores for full transparency.

Comprehensive validation reports for synthetic data

01.

Downstream performance

Measure how synthetic data performs in real AI applications. Downstream tests prove accuracy, reliability, and model compatibility.

Validation covers key metrics — accuracy, recall, precision, F1, and confidence — to confirm AI readiness and reliability.

  1. #1. Accuracy — overall correctness of predictions
  2. #2. Recall — ability to capture true positives
  3. #3. Precision — reliability of positive predictions
  4. #4. F1 — balance between precision and recall
  5. #5. Confidence — certainty of model predictions
02.

Privacy performance

Assess whether synthetic data maintains structure and perceptual consistency. Validate data integrity and human-recognizable patterns via privacy metrics.

Structural and perceptual consistency metrics confirm that synthetic data preserves schema, relationships, and natural variability — all within the high-performance range.

  1. #1. Structural — preserves form, schema, and relationships
  2. #2. Perceptual — preserves human-recognizable patterns and distributions
03.

Utility performance

Measure the usability of synthetic data in analytics and AI workflows. Confirm whether statistical distribution, diversity, and quality match the real data.

SynData benchmarks diversity, quality, and indistinguishability against the original dataset — confirming fitness for real-world use.

  1. #1. Diversity — preserves the variety of real data
  2. #2. Quality — matches the original statistical distribution
  3. #3. Indistinguishability — looks like real data

Validate synthetic data without accessing the original

  1. #1.

    Data Non-Access Technology. CUBIG's proprietary method validates data quality without ever touching the original.

  2. #2.

    Reliability guaranteed. Each report provides detailed scores for privacy, utility, and usability for transparent validation.

  3. #3.

    Backed by proven expertise. Developed by the team that authored the world's first AI security framework.