It comes built into most models and most harnesses.
Seven reasons. Thirty seconds.
Out of 23 search APIs, measured on the same queries. Updated this morning.
NEEDLE, keenableai.github.io/needle, Oct 23, 08:16 UTC · Keenable in realtime mode · p50 latency, log scale · a blink takes 100–400 ms, Harvard BioNumbers
A Keenable search fits inside that pause. A typical one doesn't.
Stivers et al., PNAS 2009: mean reply gap 208 ms · NEEDLE p50, realtime mode, Oct 23, 08:16 UTC · built into chat models: 34 s, off this slide
100B+ documents, crawled and ranked by us.
keenable.ai · every result carries its acquired time, and its published time when known (UTC)
query_time
Pick a date. Get the index as it stood then.
Point a camera at a sign or a label. Read it, then search what it says.
Voice agents whose web search fits inside the 200 ms pause between turns.
Run ten searches at once. Fill 500 rows in the background.
Check sources on a schedule. Act on whatever was acquired since the last run.
Stivers et al., PNAS 2009: mean reply gap 208 ms across 10 languages
search_web_pagesRanked results from our own index, each one dated.
fetch_page_contentAny page as clean markdown. Or ask it a question and get just the answer.
$ brew install keenableai/tap/keenable-cli $ keenable login $ keenable configure-mcp --all $ claude # or codex, cursor, opencode
BETA200.
in Keenable credits for the best build. What we're looking for:
Share what you built and tag @KeenableAI by the end of today. We'll pick one more winner from X.
Built an agent that reads a sign from a photo and looks it up live with @KeenableAI. Made today at the Beta × AWS × OpenAI hackathon.
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Join the team that already built search twice.


app.keenable.ai → Other → BETA200
docs.keenable.ai
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