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SYNTH STUDIO

Trustworthy Monetization of Data with Total Privacy

If data is the fuel for innovation, having high fidelity and privacy-protected data for the same is its lifeline. Collecting & aggregating such data for innovation, and effective AI/ML model building is expensive and time-consuming. Moreover, enterprise data sharing is severely constrained by regulatory mandates, especially when handling sensitive data like PII (Personal Identifiable Information). This necessitates meaningful alternates to create useful and effective datasets that are statistically identical to original data.

Mphasis’ Synth Studio is a patent-pending enterprise synthetic data generation solution that generates high-quality synthetic data to monetize trustworthy business insights, while preserving privacy and protecting data subjects. Its AI-generated synthetic data enables organizations to leverage data’s maximum potential to cross-collaborate and build reliable and highly accurate assets with no or minimal loss of data privacy and utility.

COMPREHENSIVE DATA SYNTHESIS

Synth Studio’s Trifecta of Performance, Privacy and Protection

Mphasis’ Synth Studio accelerates innovation by enabling organizations to build and create realistic artificial datasets through intelligent machine learning (ML) processes and models. The solution comprises two effective components — Data Synthesis and Data Enrichment.


Data Synthesis leverages artificial intelligence (AI) to create artificial data from the available representative original data, or meta-information about the data. This has 2 scenarios:

  • • Privacy-preserving synthetic data generation
    Here, synthetic data is generated as a totally privacy-safe version of the original data to unleash maximum utility for insights. Synthetic data is generated from original data while preserving its statistical properties and distributions. Existing legacy anonymization tools are inadequate to protect privacy while providing quality business insights. This module is especially useful when synthetic data is generated from original data while preserving its statistical properties and distributions.

  • • Expert-assisted synthetic data generation
    This scenario occurs when a representative sample of the original data is not available. In such cases, Mphasis’ Synth Studio creates synthetic data with the help of an expert’s assistance, based on metadata, constraints, and conditions. It covers a wide range of requirements including application testing, creation of POCs, fueling hackathons and innovation initiatives.


Data Enrichment is used to augment available data with more information to enhance its contextual utility and unlock innovation according to organizational requirements. Synth Studio accelerates data-driven innovations through joint synthesis of data and annotations, thus reducing the cognitive burden of maintaining data consistency in data preparation. It also synthesizes multi-modal data for consistently enriched data across multiple data modes, for example, X-rays with radiology reports, 3D MRI synthetization, damaged packages with assessment reports, generating tags along with images, sentiment tags for text reviews etc.


FEATURES FOR EFFECTIVE DATA UTILIZATION


Synth Studio’s versatile range of features address the gamut of requirements for synthesizing data with speed, efficiency, scale and security

 

Auto-Synthetization

An in-built integration of generative methods with other privacy strategies such as differential privacy, data anonymization etc., to intelligently select and synthesize data based on user requirements and meta data.

Auto-Synthetization

Enhanced Privacy Protection and Measurement

Through efficient model inversion, Synth Studio relentlessly protects the privacy of data subjects from adversarial attacks. With its ‘Privacy at Risk’ measurement framework, it rapidly identifies and mitigates potential risks that synthetic data can expose.

Enhanced Privacy Protection and Measurement

Conditional Synthetization

Data can be synthesized based on conditions and constraints declared by the user. In the case of tabular data, constraints can be defined either at a single-attribute level or across multiple attributes.

Conditional Synthetization

Rare-Event Synthesization

Synth Studio ‘up-samples’ rare event data in cases of limited data (such as events of financial fraud and crime), and trains ML models to detect such scenarios better. Based on user feedback, Synth Studio protects information on minority data patterns using various ML strategies.

Rare-Event Synthesization

Expert-Assisted Data Generator

AI/ML-augmented data synthesizer enables creation of synthetic data according to expert-defined cross-attribute relationships and constraints. This offloads the cognitive burden of managing the rules engine. For tabular data, multiple tables can be synthesized (primary and foreign keys) while maintaining relational coherence. It also supports diverse data structures and formats (network, image, text, etc.)

Expert-Assisted Data Generator

Evaluation Metrics for Confident Utilization

We provide statistical metrics and intuitive visualization to compare the generated dataset and the original dataset. This visibility gives organizations and users the confidence to use synthetic data for business insights and downstream analytics.

Evaluation Metrics for Confident Utilization

Close Integration with Downstream Requirements

Synth Studio customizes the synthesization process based on clearly defined purpose of downstream activities. Privacy metrics, synthetization methods and processes are integrable based on the type of dataset and nature of downstream data usage.

Close Integration with Downstream Requirements

BUSINESS BENEFITS

 

Mphasis Synth Studio’s versatile advantages deliver privacy-safe data alternatives across industries and functions.


Data Privacy Data can be shared with minimized privacy issues and with zero or very low risk of exposing consumer information.

Signal Preservation The need for masking and anonymization to protect data is significantly minimized as statistical relationships and references in the original data are removed. Only data patterns and correlations are preserved for efficiency.

Data Monetization Synth Studio creates extreme business value by making data available and usable to extract insights that are otherwise inaccessible due to data constraints, thereby enabling critical decision-making.

Speed of Innovation Synth Studio’s AI/ ML- driven features generate synthetic data at rapid speed to drive quicker innovation and place organizations ahead of the competitive curve.

IDEAS IN ACTION