Cut LLM bills by routing uncertain cases to frontier models

Cut LLM bills by routing uncertain cases to frontier models targets a $2.5B = 100,000 AI-heavy product teams x $25K ACV. Rationale: 100k potential buyers includes marketplaces, ecom platforms, content-moderation SaaS and mid-market AI-native apps that send high-volume LLM calls; $25K ACV is justified by measurable inference savings and integration value. total addressable market with low saturation and a year-over-year growth rate of 40% - driven by more SaaS products embedding LLMs and increasing price pressure on inference spend.

Key trends driving demand: LLM commoditization -- more teams adopt LLMs, creating concentrated inference spend and a new need for cost controls; Open weights and efficient models -- availability of smaller performant models enables on-prem or nearline inference for non-critical cases; Verticalization of AI -- domain-specific models and feature stores make classifiers more accurate, reducing calls to general-purpose LLMs.