New · Now Generally AvailableDataNivra — Enterprise Test Data Management, now GA
As Chief AI/Data Architect at DataNivra, I designed and built an enterprise-grade Test Data Management (TDM) platform that has grown from a single enterprise deployment into a generally available, self-service product with a React-based front end. A customer-resident agent performs all discovery, masking, and synthesis inside the customer's own security boundary — only control metadata and policy evidence reach the DataNivra cloud, never raw data rows or secrets — which is what makes it suitable for hospitals and health systems, tax and auditing firms, banks, and insurers working with PHI, PII, and other regulated data. The platform now ships Python and TypeScript SDKs, native CI/CD integrations (GitHub Actions, GitLab CI, Jenkins, Azure DevOps, CircleCI, and more), and a local MCP adapter so AI coding and QA agents can request certified test data the same way a human or pipeline does.
PHI / PII Discovery & Masking27+ Source ConnectorsCI/CD NativeAI Agent / MCP IntegrationPython & TypeScript SDKsHealthcare · Finance · Insurance · more
The core DataNivra platform codebase remains private, but runnable examples, CI/CD recipes, and an MCP adapter for AI agents are public in the datanivra-examples repository (MIT-licensed). The SDKs and supporting tooling are now distributed as installable packages: datanivra-sdk, datanivra-cli, datanivra-mcp, and datanivra-contracts on PyPI (pip-installable), and @datanivra/sdk and @datanivra/contracts on npm.
