Slash the hidden 43% of LLM API spend — detect, attribute & auto-tune

Slash the hidden 43% of LLM API spend — detect, attribute & auto-tune targets a $36.0B = 3.0M developer orgs x $12K avg annual LLM API spend total addressable market with medium saturation and a year-over-year growth rate of 70% projected annual growth in enterprise LLM API spend and related tooling.

Key trends driving demand: Model proliferation -- many providers/models increase variance in cost/quality per call, creating arbitrage opportunities for routing & selection.; API-driven apps -- rapid integration of LLMs into product workflows turns token spend into a predictable ops cost that teams want to optimize.; MLOps-to-llmops convergence -- observability and monitoring best practices are being applied to generative models, enabling similar tooling.; Serverless & edge inference -- cheaper execution options make dynamic routing and caching strategies practical at scale..