Linkup
Production web search API for AI — sub-second cited search, page fetch and async deep research
0About Linkup
Linkup is a production-grade web search API built specifically as the retrieval layer under AI applications, rather than a consumer search engine with an API bolted on. It exposes three primitives with deliberately different latency and cost profiles: Fetch, which extracts the content of a given page in under two seconds; Search, which returns sourced, cited results with full-text snippets in one to three seconds and is the primitive an agent calls mid-loop; and Research, an asynchronous deep-research endpoint that runs for one to ten minutes on complex questions. You keep control of the index rather than accepting a black box — tuning which sources are in scope and how fresh results must be — and the whole thing can be deployed inside your own cloud when data residency matters. Accuracy is published against benchmark datasets including SimpleQA, with a methodology page rather than a bare claim. The company positions around four uses: giving agents real-time cited web access through one vendor instead of several; legal research where full regional data residency is non-negotiable; sales enrichment that resolves a company at signup and surfaces live buying signals; and reinforcement learning, where training a search agent on the same retrieval engine you ship in production gives a denser reward signal and cuts tokens, turns and searches. SDKs ship for Python and Node.js alongside plain cURL, and SOC 2 Type II is included on every plan.
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Key Features
Linkup Pros & Cons
✅ Pros
- +Per-request pricing with no platform fee makes cost trivially forecastable
- +4,000 free queries is a real evaluation, not a demo
- +Published benchmark methodology instead of an unsourced accuracy claim
⚠️ Cons
- −Research at up to $2.50 a call gets expensive fast in an agent loop
- −Prices are quoted as ranges, so worst-case is what you should budget
- −Self-hosted deployment and ZDR are Enterprise-only
Tags
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