Synthetic Data Generation Tools
One-stop solution for preparing, generating, and managing compliant,
realistic, and accurate data for software testing and ML model training
SYNTHETIC DATA GENERATion TOOLS
Generate realistic, accurate, and compliant data
Business entity approach
Enforce referential integrity of the generated data by applying a data model blueprint.
4 data generation techniques
Control how test data is created using any combination of synthetic data generation methods.
Self-service portal or APIs
Empower teams to generate and integrate synthetic data into CI/CD and ML pipelines.
Entity-based data generation
enforces referential integrity
K2view synthetic data generation is a one-stop solution for preparing, generating, and managing compliant, realistic, and accurate data for software testing and ML model training. It generates synthetic data by business entities (such as customer, device, order, etc.), ensuring that all the required data for each business entity is consistent and contextually accurate.
The business entity model serves as the blueprint for generating synthetic data, regardless of the method. It automatically discovers and classifies data formats, structures, and types – while enforcing referential integrity across all source systems.
maximizing accuracy and compliance
Combining all 4 data generation methods
- 01 Generative AI
- 02 Rules engine
- 03 Entity cloning
- 04 Data masking
For data augmentation
- Subset the data needed for model training.
- Mask training data to ensure compliance.
- Train the GPT model based on masked data subsets.
- Generate the synthetic data.
- Apply business rules for increased accuracy.
For functionality/negative testing
- Automatically create entity model data generation functions.
- Customize, test, and debug the functions, code free.
- Empower users to set up the business parameters.
- Generate data on demand or via API.
For performance/load testing
- Instantly generate large datasets.
- Extract, mask, and clone a single business entity and all its data.
- Create unique identifiers for each cloned entity.
For all data protection use cases
- Auto-discover Personally Identifiable Information (PII).
- Apply prebuilt, customizable data masking functions.
- Mask data inflight, as it's extracted from the sources.
Going beyond data generation
Management of the entire
synthetic data lifecycle
K2view has the only end-to-end synthetic data management solution, supporting data preparation, data pipelining, and data operations.
Provision compliant data subsets, code-free.
Mask and transform the data, in flight.
Reserve data subsets for individual users.
Version and roll back datasets on demand.
Integrate data into CI/CD and ML pipelines via APIs.
Synthetic data generation tools
for augmentation when data is scarce
for functionality and negative testing
for performance and load testing
for all data protection use cases
of all data types, sources, and formats
for a blueprint of the data to be generated
directly from the source systems
directly into target systems