From QA engineers to assurance officers to auditors: one Markdown format, shared accountability
Oversee governance requirements and audit preparation with structured, queryable evidence. Define what needs validation based on risk and regulatory requirements.
Execute validation and assurance testing with plain text and Git. No more wrestling with proprietary test management UIs.
Implement controls and keep validation tests next to source code. Test logic and implementation evolve together.
Automate assurance gates and verify configurations reproducibly. Every test run is auditable and repeatable for governance.
Execute computer system validation and GxP testing with complete documentation. Work in air-gapped environments when required.
Access verifiable evidence directly with SQL queries. No screenshots, no manual reports, no data reconstruction.
Assurance defines requirements. QA executes. Developers implement. SREs automate. Auditors verify. All working from the same Markdown tests with shared accountability, versioned in Git, and stored with integrity in surveilr.
Because tests are Markdown, AI can generate validation protocols from requirements, review completeness against regulatory frameworks, and summarize evidence for audit reports. Ask AI to "generate FDA validation test cases from this URS" or "summarize all SOC 2 control test failures" and get actionable assurance insights instantly.