Prevent LLM JSON breakage: schema-driven benchmarking and repair guidance

Prevent LLM JSON breakage: schema-driven benchmarking and repair guidance targets a $6.0B = 100,000 enterprises x $60K ACV (enterprise LLM-evaluation & observability suites) total addressable market with medium saturation and a year-over-year growth rate of 35%+ (enterprise AI tooling & MLOps growth).

Key trends driving demand: Enterprise LLM adoption -- more teams using LLMs for structured workflows increases demand for reliability tooling.; Shift to production-grade ML -- teams expect observability, testing, and CI/CD parity for LLMs similar to traditional services.; Model diversity & vendor switching -- multi-vendor strategies force tooling that is model-agnostic and compares outputs under real schemas.; Regulatory/compliance focus -- structured data and audit trails create demand for deterministic, verifiable output guarantees..