PII and Data Balancing

Protect privacy and keep datasets fair, representative, and production-ready

Protect privacy and keep datasets fair, representative, and production ready.

Automatically detect and mask sensitive data, decontaminate splits, and balance cohorts through blending, shuffling, and stratification so your models stay compliant and reliable.

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Key Capabilities

Sensitive Data Protection

Remove sensitive identifiers before training or sharing.

Bias-Free Modeling

Prevent skewed cohorts from driving biased predictions.

Stable Evaluation Splits

Balanced, decontaminated splits = stable, reproducible metrics.

Tests

An overview of all tests

PII Detection & Masking

Find and anonymize sensitive text without losing task context.

ML entity recognition + rules/regex for domain formats.

Redaction, hashing, or tokenized placeholders (configurable).

Audit trail with examples and category counts.

Blending/Shuffling

Keep cohorts representative and evaluation fair.

Class/segment stratification, min-count guarantees.

Source blending with target ratios (e.g., 60/40 support vs FAQ).

Deterministic shuffling to remove order bias and ensure reproducibility.

Quality Filtering & Deduplication

Image Classification

CUSTOMER CASE STUDY

Leading Portfolio medical technology company working with pre Operative data quality assurance

72%

Reduction in DICOM header rejections

1.3x

Improvement in model performance from automated quality checks

5x

Speedup in Human in the Loop(HIL) review process

45%

Poor quality scans automatically flagged

CUSTOMER CASE STUDY

Leading Portfolio medical technology company working with pre Operative data quality assurance

72%

Reduction in DICOM header rejections

1.3x

Improvement in model performance from automated quality checks

5x

Speedup in Human in the Loop(HIL) review process

45%

Poor quality scans automatically flagged

Protect privacy and keep datasets fair, representative, and production-ready

Protect privacy and keep datasets fair, representative, and production ready.

Key Capabilities

Sensitive Data Protection

Bias-Free Modeling

Stable Evaluation Splits

An overview of all tests

PII Detection & Masking

Blending/Shuffling

CUSTOMER CASE STUDY

Leading Portfolio medical technology company working with pre Operative data quality assurance

72%

1.3x

5x

45%

CUSTOMER CASE STUDY

Leading Portfolio medical technology company working with pre Operative data quality assurance

72%

1.3x

5x

45%

Join 5,000+ companies growing with RagaAI

Join 5,000+ companies growing with RagaAI

Join 5,000+ companies growing with RagaAI