Fragmented one-off LLM eval scripts → composable, sandboxed eval framework

Fragmented one-off LLM eval scripts → composable, sandboxed eval framework targets a $6.0B = 200,000 AI-using engineering teams x $30,000 ACV on evaluation, monitoring & governance tooling total addressable market with medium saturation and a year-over-year growth rate of 35%+ annual growth driven by LLM adoption and MLOps spend.

Key trends driving demand: LLM proliferation -- more teams deploying generative models increases need for systematic evals and regression tracking.; Shift to composable tooling -- modular, interoperable components let orgs adopt eval tooling incrementally.; Model governance & auditability -- regulatory and procurement requirements push for reproducible evals and secure execution logs..