Keenable
Keenable is an independent web search infrastructure for AI agents and labs, exposing low-latency APIs for fresh results, cleaned page content retrieval, and point‑in‑time search. Built for high RPS, dedicated capacity, and cloud or on‑prem deployment to support production inference.
Overview
Agents issue search queries, receive ranked links with scores and snippets, then fetch cleaned page content to ground answers or build context windows. Time Machine anchors retrieval to a chosen query_time, enabling reproducible chains-of-thought, audits, and evaluation runs as the live web evolves.
Core Capabilities
Keenable suits engineering teams shipping retrieval‑augmented generation, agentic browsing, research copilots, and monitoring systems that require stable, auditable search. AI labs, inference providers, and enterprise platform teams can integrate it as a managed backend, avoiding the complexity of web crawling, deduplication, freshness workflows, and ranking. Builders benefit from predictable performance for evaluation harnesses, A/B testing, and compliance reviews, especially when temporal reproducibility via Time Machine is required.
- Retrieve ranked web results with metadata from a continuously updated large index.
- Fetch normalized page text for quoting, reranking, summarization, and model grounding.
- Anchor searches to historical snapshots using query_time for reproducible experiments.
- Scale to high RPS with dedicated capacity and predictable throughput guarantees.
- Deploy in cloud or on‑prem environments to meet data residency requirements.
Highlights
Differentiators and Considerations
Sign up in the Console to obtain an API key, then integrate the Search API for ranked links and the Fetch Page Content endpoint for normalized text. Use Time Machine by adding a query_time parameter when you need reproducible, historically anchored outputs. The Agent Builder Tier is cloud‑only, offers a free 100K‑request allowance, and pay‑as‑you‑go pricing. Frontier Tier unlocks dedicated capacity, higher sustained RPS, and cloud or on‑prem deployment. Documentation includes endpoint parameters and example requests so teams can prototype quickly before moving to production.
A production‑ready search backend that prioritizes latency, scale, and temporal reproducibility over marketing gloss.
Getting Started
Keenable stands out as a focused web search backend for AI systems: large index, low latency, predictable capacity, and a native temporal model for reproducibility. Teams avoid operating crawlers and parsers, lean on consistent APIs, and scale from free builder quotas to dedicated RPS. If you need controllable cost‑quality tradeoffs and verifiable grounding across changing pages, Keenable is a pragmatic fit.
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Keenable
Keenable is built by a search‑infrastructure team led by Andrey Styskin (ex‑CEO of Search & Ads at Yandex; Director of Web Infra at Amazon AGI) and Matthias Petri (ex‑Principal Applied Scientist at Amazon AGI). The team previously built Alexa’s web grounding service and a trillion‑token index for large‑scale retrieval.
Keenable provides a production-grade web search backend purpose-built for LLM agents and inference platforms. A large, continuously learned index (100B+ documents) and sub-250ms p95 latency in US East enable responsive, grounded workflows at scale. Developers call the Search API to retrieve ranked results and metadata, then use the Fetch Page Content API to pull normalized page text for quoting, citation, or reranking. Time Machine adds a query_time parameter, letting teams search historical snapshots and reproduce answers as pages change. Capacity is available as shared cloud for builders or dedicated Frontier capacity with higher RPS, predictable throughput, and cloud or on‑prem deployment. Public comparisons on the NEEDLE benchmark emphasize a cost–quality profile aimed at high-volume use. Keenable focuses on stable APIs, operational reliability, and straightforward pricing so teams can ship search‑augmented systems without operating their own crawler, index, or ranking stack.
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