Launched this week
Auriko treats LLM providers as trading venues and arbitrages the spread. Built by ex-quant traders, Auriko’s cost-arbitrage engine calibrates to each user’s request patterns and selects optimized inference paths based on token price, cache behavior, latency, reliability, and request quality. Auriko benchmarks show average 30% cost reduction against industry peers and direct providers. See the source: https://www.auriko.ai/reports/llm-cost-arbitrage
Tate-A-Tate
Love the "trading desk for inference" framing—routing on cache behavior and real-time provider signals instead of just headline prices is exactly the kind of optimization most teams skip, and the zero-markup model makes it a no-brainer to try. Congrats on the launch! 🚀
Auriko
@eeeeeach Thanks!
Ada.im
Nice launch! LLM cost optimization is exactly where a lot of teams need help right now.
@zxy_action1 Congratulations and happy product hunt.
Macaly
llm calls as a trading desk is such a clever framing 📈 30% savings is a real hook, congrats on #1