Octen Unveils AI-Optimized Search API at 62ms Latency
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Search was designed around 1 human entering 1 query and checking results. AI agents do not use it like that. They explore 1 question through 50 paths at once. Today’s search APIs still copy the same human process through an endpoint. Octen rebuilt the stack for machines: index, ranking, and serving layer. 62ms per search. $1 per 1,000 calls. The interface moved on long ago. The engine is finally there too.
Search was designed around 1 human entering 1 query and checking results. AI agents do not use it like that. They explore 1 question through 50 paths at once. Today’s search APIs still copy the same human process through an endpoint. Octen rebuilt the stack for machines: index, ranking, and serving layer. 62ms per search. $1 per 1,000 calls. The interface moved on long ago. The engine is finally there too.
the problem your agent fires 50 searches to answer one question. each one waits on a search api built for a human typing a single query. that's the bottleneck nobody profiles until latency starts spiking in production. → what caught my eye it's not the 62ms on sealqa hard, though that's fast. it's that octen's spread between p50 and p90 is 6ms. some search apis swing over a full second between those two. an agent can't plan around a search it can't predict. → why it matters at 62ms with almost no variance, search stops behaving like a tool you call and starts behaving like memory you read. that quietly changes how you'd architect the whole loop.