Automatically test row-level DB access policies using generated test cases

Many engineering and security teams struggle to validate row-level access controls (RLS) and database access policies, so bugs that block or overexpose rows often slip into production; this is especially painful for mid-size and larger software orgs with multi-tenant schemas and complex RBAC. The immediate audience is the estimated 130,000 mid+ software companies that could buy security tooling, where a single RLS misconfiguration can cause compliance failures, data breaches, and high remediation costs. You could build an automated testing platform that parses policy-as-code and DB configs (Postgres, Supabase, Neon), synthesizes targeted row-level test cases, runs them in ephemeral sandboxes or CI pipelines, and outputs coverage metrics, failing assertions, and concrete remediation guidance. Market timing is favorable: hosted Postgres and cloud-native DBs are making RLS mainstream, shift-left security is driving test automation into CI, and a $6.5B addressable market (130,000 orgs × $50K ACV) with a market score of 90/100 and revenue potential of 88/100 indicates strong commercial opportunity. To stand out you must minimize false positives/negatives, demonstrate measurable policy-coverage (for example, percent of policy branches exercised), and provide deep integrations with policy-as-code, infra repos, and existing test runners so developers treat it as part of their workflow rather than a separate security ticketing step. The challenges are real—generating realistic test data, safely accessing production-like schemas and secrets, and keeping up with varied policy languages—so competitors are medium but the focused value proposition (preventing high-impact data incidents for ~$50K ACV customers) gives a clear path to differentiation if the product nails accuracy and developer experience.