Prevent SQL injection in analytics queries with typed, engine-aware SQL fragments

Prevent SQL injection in analytics queries with typed, engine-aware SQL fragments targets a $3.0B = 100,000 analytics-enabled companies (mid-market + enterprise) x $30K ACV for developer-friendly analytics-safety tooling total addressable market with medium saturation and a year-over-year growth rate of 15% - increased spend on data-security and developer-security tooling as analytics adoption grows.

Key trends driving demand: Generative AI in apps -- LLMs routinely produce SQL or otherwise control query inputs, increasing the risk surface for injection via dynamic text; Rising ClickHouse adoption -- ClickHouse growth in observability/self-hosted analytics introduces engines lacking mature parameterization patterns; Shifting developer expectations -- demand for compile-time guarantees and small, composable libraries that work inside type systems; Privacy & compliance focus -- companies investing more in runtime/data access controls and query sanitization because of regulatory scrutiny.