Keenable searches our own 100B+ page index. We are focused on low cost and latency (p95 <250ms from us-east). We don’t believe in benchmaxxing, so we open-sourced our internal benchmarking suite, NEEDLE (available at https://keenableai.github.io/needle): a live benchmark that compares Keenable with other search APIs on fresh agent-like queries.
I spent seven years at Amazon as a scientist working on web grounding for Alexa/AGI, and my co-founder Andrey previously led search at Yandex. We started Keenable because agents search differently from humans, and we wanted to build around those patterns directly.
The API is available now and we provide a free allowance of 100,000 requests a month.
It also exposes a novel SQL-like interface to the web, which is useful for structured extraction and agent workflows.
Happy to answer questions about the index, crawl, ranking, latency, or benchmarking.
styskin•28m ago
matt4711•4m ago
This provides interesting tradeoffs where models can call search much more frequently which we believe is one thing that is not happening today.
Our benchmarks (see https://keenableai.github.io/needle/card-lowshared/ ) also suggest that some players in the market, such as Parallel and Brave, may be using the same underlying search index.