卖什么
Self-optimizing neocloud that cuts LLM costs by 100x
商业模式拆解
买家：谁掌握预算？
未核实Heads of AI/engineering at companies running high-volume LLM workloads (agents, extraction, labeling).
工作流：什么输入变成什么输出？
Observe production traces and expert corrections, evaluate models against held-out examples, improve via prompts or a trained specialist model, then deploy when quality, cost and latency targets are met.
经济账：省了什么，怎么收费？
Claims 83.4% lower inference cost per task than a frontier baseline ($0.000074 vs $0.000444); customers always own fine-tuned weights.
渠道：怎么接触到客户？
Sales-led: "Talk to Orchestra" / contact form; no self-serve pricing shown.
融资历史与报道
| 融资日期 | 轮次 | 金额 | 投资方 | 来源 |
|---|---|---|---|---|
| — | YC 2026 夏季 | — | Y Combinator | ycombinator.com |
档案汇总自公开报道和公司官网。商业模式部分是 MaxBC 对这些材料的解读，不是已确认的事实；未知之处留空，不作猜测。 更新于 2026-10-12.