How Linkup Scales AI-Native Web Search with Cerebrium

Linkup, a web search API designed to provide AI agents with fresh, structured web information, uses Cerebrium’s serverless GPU infrastructure to support real-time retrieval, embedding, and reranking workloads for customers including sales, legal, research, and enterprise-search applications. As its usage expanded globally, Linkup needed rapid GPU scaling, low-latency regional processing, data-residency support, and flexible deployment for frequently changing models and custom containers. Cerebrium enabled Linkup to independently scale workloads across GPU types, use checkpointing to reduce worker startup times by more than 60% to a few seconds, and deploy closer to users in the United States and Europe to reduce network delays. Its multi-region routing and deployment capabilities also support regional data processing and resilience, while custom container support lets Linkup’s ML team test models and configurations without managing underlying infrastructure. According to Linkup, the arrangement has allowed its teams to focus more on search quality, latency, reliability, and cost rather than GPU operations.

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