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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.


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.


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




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.