The value of data is multi-dimensional and limitless. Amidst opportunities, there is one vital and non-negotiable requirement – data security. With data security as a critical backdrop, gaining access to high-quality data for testing within the bounds of confidentiality and privacy proves to be a challenge along the software testing lifecycle. Synthetic data offers a time and cost-efficient solution, preventing bottlenecks in development workflows and enabling accelerated testing.
Mphasis Synth Studio is a patent-pending enterprise synthetic data solution designed to revolutionize software testing. It generates high-quality synthetic data to accelerate software testing workflows tailored to specific test scenarios. Synth Studio emphasizes testing efficiency and precision in quality assurance. It enables teams to validate models and benchmark performance using realistic, privacy-safe datasets, even in environments where access to real data is restricted due to compliance or confidentiality concerns.
Synthesizing data with speed, efficiency, scale, and security
Software Testing Lifecyle Mapping
Modules aligned to enhance the test data requirement phase of the testing lifecycle. It facilitates accurate definition of test data requirement, boundary values, ensuring the data generated meets the input criteria.
Diverse Data Generation
Diverse synthetic datasets that match with defined data specifications & constraints, enabling robust testing and reliable analysis across varied use cases by supporting boundary value generation and constraint-based data synthesis.
Pairwise Testing Data Synthesizer
Data generation to cover all possible pairwise combinations of input parameters and enhances test coverage, while minimizing the number of test cases.
Truth Table & Data Enhancing Synthesizer
Gen AI-led validation of generated data to ensure ability to handle all the possible test scenarios (positive & negative), defined as part of constraints or rules, which enables swift and structured analysis of test conditions.
Overcomes limitations of incomplete data by appending synthetic data to existing data sets and validating it against defined constraints which ensure continuity and completeness in test scenarios.
Auto Synthesization
In-built integration of generative methods with other privacy strategies such as differential privacy, data anonymization, etc.
Mphasis Synth Studio transforms software testing by generating high-quality synthetic data—securely, swiftly, and intelligently. It empowers teams to test confidently, innovate faster, and deliver better software outcomes.
Accelerated Testing Cycles :
Our synthetic data solution, Mphasis Synth Studio transforms software testing by generating high-quality synthetic data-securely, swiftly, and intelligently. It empowers teams to test confidently, innovate faster, and deliver better software outcomes.
Data privacy :
Enables data-safe testing without exposing sensitive consumer information by integrating privacy-preserving techniques like anonymization and differential privacy.
Efficiency and Precision in Test Coverage :
Generates data customized to test scenarios, acceptance criteria, and boundary conditions, enhancing coverage through pairwise testing that efficiently addresses all pairs of input parameter combinations.
Enables Robust Testing :
Synthesizes data covering extensive testing scenarios, including edge cases that might be rare or unavailable in real datasets.
Enhances Compliance & Security :
Synthetically generated data eliminates the exposure of real personal information, enabling businesses to comply with privacy regulations such as GDPR and HIPAA, while mitigating the risks associated with data breaches.
Accelerates Innovation :
Enables faster testing and development cycles by providing abundant, readily available data without waiting for real data collection.
Privacy concerns make access to secure, high-quality data a challenge for organizations. Synthetic data solutions generate high-quality synthetic data, offering organizations a safe alternative for testing and innovation. Mphasis Synth Studio is a patent-pending synthetic data generation solution that helps accelerate testing, analytics, and innovation, while protecting sensitive information.
As organizations make the move towards being AI-first, their initiatives require large, representative datasets to develop and validate AI models. Synthetic for AI data mirrors real-world characteristics, while preserving privacy. Mphasis Synth Studio uses AI-driven techniques to create realistic datasets for testing, analytics, and AI model validation.
Developing AI models and solutions is often met with challenges due to limited availability of data, compliance issues, and privacy concerns. Leveraging synthetic data helps address these challenges by offering realistic datasets that are secure, enabling quality model training and validation.
Diverse, high-quality, representative datasets are crucial for machine learning models to deliver reliable results. Synthetic data generation solutions like Mphasis Synth Studio can accelerate machine learning model development by generating realistic synthetic datasets that help build accurate models, while reducing the dependence on sensitive real-world data.
Establishing privacy guardrails is crucial while generating synthetic datasets. Mphasis Synth Studio generates secure synthetic data by integrating techniques such as data anonymization and differential privacy. This allows for secure testing and innovation, while adhering to privacy regulations.
Synthetic data solutions are relevant across industries that benefit from large scale data models. Especially in regulated industries such as healthcare and finance, where data sensitivity and privacy are crucial concerns, synthetic data solutions find numerous applications.
