Detecting LLM API Drift - continuous monitoring and alerts

Detecting LLM API Drift - continuous monitoring and alerts targets a $6.0B = 100,000 AI-using companies x $60K ACV. Rationale: surveys show tens of thousands of companies integrating LLMs; observability for critical infra commands enterprise-grade pricing. total addressable market with medium saturation and a year-over-year growth rate of 35% annual growth in AI ops and model observability demand driven by LLM adoption.

Key trends driving demand: Rapid LLM releases -- frequent model updates from major providers create continuous drift risk and a need for monitoring.; Third-party model reliance -- companies increasingly consume hosted LLM APIs rather than self-hosting, shifting control to vendors.; MLOps convergence -- teams reuse observability patterns from ML for LLMs, opening workflows for drift detection and automated testing..