The Global Leading Institution for Synthetic Data Validation
The Global Leading Institution for Synthetic Data Validation
The Global Leading Institution for Synthetic Data Validation
The Global Leading Institution for Synthetic Data Validation
Delivering insightful reports with the safest approach to synthetic data validation
Delivering insightful reports with the safest approach to synthetic data validation
Delivering insightful reports with the safest approach to synthetic data validation
Delivering insightful reports with the safest approach to synthetic data validation
Validate Synthetic Data Without Touching Original Data
Validate Synthetic Data Without Touching Original Data
Validate Synthetic Data Without Touching Original Data
Validate Synthetic Data Without Touching Original Data
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
The Only Certified Synthetic Data Validation Agency in Korea
The only institution in Korea authorized to validate compliance with PIPC (Personal Information Protection Commission) guidelines
Receive your validation report
within a
1-day
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
The Only Certified Synthetic Data Validation Agency in Korea
The only institution in Korea authorized to validate compliance with PIPC (Personal Information Protection Commission) guidelines
Receive your validation report
within a
1-day
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
The Only Certified Synthetic Data Validation Agency in Korea
The only institution in Korea authorized to validate compliance with PIPC (Personal Information Protection Commission) guidelines
Receive your validation report
within a
1-day
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Zero Original Data Access
Validate with CUBIG’s data Non Access Tech No risk of original data exposure.
The Only Certified Synthetic Data Validation Agency in Korea
The only institution in Korea authorized to validate compliance with PIPC (Personal Information Protection Commission) guidelines
Receive your validation report
within a
1-day
Validation Report
Receive your validation report in as little as 1 hour! or within a day!
Insightful Premium Reports
Insightful Premium Reports
Insightful Premium Reports
Insightful Premium Reports
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Performance Metrics
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Cost-Effciency Lists
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Cost-Effciency Lists
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Performance Metrics
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Cost-Effciency Lists
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
01.
Downstream The Definitive Test for AI-Ready Synthetic Data
Measure your data’s real-world impact on AI performance through key downstream metrics.
Performance Metrics
Accuracy: Measures overall correctness of predictions
Recall: Identifies how well true positives are captured
Precision: Ensures reliability of positive predictions
F1 Scrore: Balances precision & recall for a fair assessment
Confidence: Evaluates certainty in model predictions
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Privacy Performance
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Cost-Effciency Lists
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Cost-Effciency Lists
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Privacy Performance
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Cost-Effciency Lists
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
02.
Privacy Performance Ensuring Structural Integrity and Perceptual Consistency
Evaluate whether synthetic data maintains its original structure and human-perceived quality through privacy performance metrics.
Privacy Performance
Structure: Maintains data format, schema, and relationships
Perceptual: Preserves human-recognizable patterns & dists
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Utility Performance
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Cost-Effciency Lists
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Cost-Effciency Lists
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Utility Performance
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Cost-Effciency Lists
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
03.
Utility Performance Validating the Real-World Usability of Synthetic Data
Assess how well synthetic data supports real-world analysis, maintains statistical distributions, and aids AI-driven decision-making.
Utility Performance
Diversity: Maintains the variety of real data
Quality: Ensures statistical similarity to original data
Indistinguishability: Real-data-like authenticity
The First and Only Institution Validating Synthetic Data Without Originals
The First and Only Institution Validating Synthetic Data Without Originals
The First and Only Institution Validating Synthetic Data Without Originals
The First and Only Institution Validating Synthetic Data Without Originals
Data Non Access Tech
Data Non Access Tech
Data Non Access Tech
Data Non Access Tech
Only Cubig leads with this proprietary innovation among synthetic data companies
Only Cubig leads with this proprietary innovation among synthetic data companies
Only Cubig leads with this proprietary innovation among synthetic data companies
Only Cubig leads with this proprietary innovation among synthetic data companies
The Most Reliable Way
The Most Reliable Way
The Most Reliable Way
The Most Reliable Way
Assess data quality with detailed scoring on safety, usability, and more
Assess data quality with detailed scoring on safety, usability, and more
Assess data quality with detailed scoring on safety, usability, and more
Assess data quality with detailed scoring on safety, usability, and more
With AI Security Leaders
With AI Security Leaders
With AI Security Leaders
With AI Security Leaders
Pioneered by CEO who wrote the first AI security paper in the world
Pioneered by CEO who wrote the first AI security paper in the world
Pioneered by CEO who wrote the first AI security paper in the world
Pioneered by CEO who wrote the first AI security paper in the world
Trustworthy Data Starts Here Get Verified with SYNDATA
Safe, simple, and exclusive entrust your synthetic data to CUBIG.
Trustworthy Data Starts Here Get Verified with SYNDATA
Safe, simple, and exclusive entrust your synthetic data to CUBIG.
Trustworthy Data Starts Here Get Verified with SYNDATA
Safe, simple, and exclusive entrust your synthetic data to CUBIG.
Trustworthy Data Starts Here Get Verified with SYNDATA
Safe, simple, and exclusive entrust your synthetic data to CUBIG.