Reduce LLM eval costs with smart proxies, caching, and sampling

Reduce LLM eval costs with smart proxies, caching, and sampling targets a $4.5B = 1.5M developer and data teams × $3K ACV total addressable market with medium saturation and a year-over-year growth rate of 30% YoY growth — LLMops and developer tooling demand (source: market reports from Gartner/IDC and public LLMops startups).

Key trends driving demand: Trend — LLM-based agents and multi-tool chains dramatically increase per-run API and tool-call volume, creating operational cost pressure that teams want to reduce.; Trend — Explosion of LLMops and experiment-tracking tools means teams are ready to adopt tooling that integrates into CI and dev workflows.; Trend — Improved small/efficient model proxies and distillation techniques make it viable to run cheaper approximations for evaluation without losing signal.; Trend — Companies prioritize developer velocity and cost control together, so a tooling solution that improves both will be well-received..