Problem

Enterprise engineering and QA teams need test data that behaves like production without copying sensitive customer or operational data into non-production environments. Traditional provisioning is slow, manual, difficult to scale across complex databases, and creates compliance risk; the result is a test-data bottleneck that delays releases, migrations, and defect discovery. Synthesized cites savings of more than 70% across an application’s development and test lifecycle, while a customer case reports 10x faster provisioning after replacing manual workflows.

The clearest use case is continuous enterprise testing: creating realistic, compliant data for application releases, SAP transformations, and end-to-end validation of AI agents before they reach production. For SAP HANA environments in particular, tightly integrated data can be difficult to reproduce without affecting business continuity, making safe, production-scale test data especially valuable.

Product / Service

Synthesized provides an AI-native test-data-management and data-automation platform. Teams connect a database schema, sample, application API, or production database; configure a workflow through a visual editor or CLI; and then automatically mask sensitive fields, subset large databases, or generate synthetic data before deploying it into test or pre-production environments. The platform is designed to preserve referential integrity, statistical patterns, business rules, and database relationships rather than producing simplistic “fake” records.

The service integrates with CI/CD pipelines so test data can be refreshed and provisioned on demand. It supports cloud, on-premises, and hybrid deployment models, including customer-controlled infrastructure, which reduces the need to move source code or sensitive data to Synthesized. The benefit is faster, repeatable testing with stronger privacy controls and less manual engineering work; the company says customers can achieve faster test cycles, lower infrastructure and operational costs, and broader test coverage.

Market

Synthesized competes across test data management, synthetic data generation, DataOps, and AI-driven software testing. Its closest named competitors include Delphix, Tonic, and Gretel: Delphix emphasizes virtualized delivery of masked production data, Tonic focuses on synthetic database mimicking, and Gretel offers AI-generated data through developer-oriented APIs. Synthesized differentiates around automated masking, subsetting, and generation for complex enterprise databases, CI/CD integration, SAP-native workflows, and deployment inside regulated customers’ environments.

The company shows commercial traction rather than appearing pre-revenue. It reports use by major enterprises including Deutsche Bank and UBS, sells to large regulated organizations on a B2B subscription basis, and has published customer outcomes such as 10x faster test-data provisioning at a UK university. In September 2025 it raised a $20 million Series A led by Redalpine Venture Partners, with participation from IQ Capital, Mercia Ventures, UBS, Seedcamp, and Deutsche Bank. Public evidence confirms customers, funding, and measurable deployments, although it does not disclose a revenue figure.