AI Verse
When real-life data capture is challenging, we generate diverse, fully labeled image datasets.
Our procedural technology ensures the highest quality, unbiased, labeled synthetic datasets that will improve your computer vision model’s accuracy. AI Verse empowers users with full control over scene parameters, ensuring you can fine-tune the environments for unlimited image generation, giving you an edge in the competitive landscape of computer vision development.
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Sixpack
Sixpack is a data management platform designed to streamline synthetic data for testing purposes. Unlike traditional test data generation, Sixpack provides an endless supply of synthetic data, helping testers and automated tests avoid conflicts and resource bottlenecks. It focuses on flexibility by enabling allocation, pooling, and instant data generation while keeping data quality high and privacy intact.
Key features include easy setup, seamless API integration, and the ability to support complex test environments. Sixpack integrates directly with QA processes, so teams save time on managing data dependencies, minimize data overlap, and prevent test interference. Its dashboard offers a clear view of active data sets, and testers can allocate or pool data according to project needs.
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GenRocket
Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.
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IRI FieldShield
IRI FieldShield® is powerful and affordable data discovery and masking software for PII in structured and semi-structured sources, big and small. Use FieldShield utilities in Eclipse to profile, search and mask data at rest (static data masking), and the FieldShield SDK to mask (or unmask) data in motion (dynamic data masking).
Classify PII centrally, find it globally, and mask it consistently. Preserve realism and referential integrity via encryption, pseudonymization, redaction, and other rules for production and test environments.
Delete, deliver, or anonymize data subject to DPA, FERPA, GDPR, GLBA, HIPAA, PCI, POPI, SOX, etc. Verify compliance via human- and machine-readable search reports, job audit logs, and re-identification risk scores.
Optionally mask data as you map it. Apply FieldShield functions in IRI Voracity ETL, federation, migration, replication, subsetting, or analytic jobs. Or, run FieldShield from Actifio, Commvault or Windocks to mask DB clones.
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