Logo Icon Linkup

How to Evaluate Web Search for AI Systems

How to Evaluate Web Search for AI Systems

Denis Charrier / CTO & Co-founder

Denis Charrier / CTO & Co-founder

Why most AI web search evaluations are broken and how it's holding your AI system back


Every AI system - from RAG pipelines to autonomous agents - lives or dies by what it retrieves. Yet most teams pick their web search provider based on gut feel or a handful of test queries. This guide will give you the framework to change that.

Linkup's evaluation framework gives you a structured, reproducible method to benchmark web search APIs against your own data - not generic leaderboards. Inside, you'll find:

Every AI system - from RAG pipelines to autonomous agents - lives or dies by what it retrieves. Yet most teams pick their web search provider based on gut feel or a handful of test queries. This guide will give you the framework to change that.

Linkup's evaluation framework gives you a structured, reproducible method to benchmark web search APIs against your own data - not generic leaderboards.
Inside, you'll find:

  • A three-tier evaluation system that scales from a quick, free sanity check (BERTScore + entity coverage) to a statistically rigorous analysis with confidence intervals and significance testing - so you invest exactly the effort the decision warrants.

  • Practical dataset design guidance - how many queries you actually need (hint: at least 200), how to stratify them across factual, time-sensitive, multi-hop, and domain-specific categories, and why your own production traffic is the most valuable input.

  • Multiple independent scoring systems covering faithfulness, completeness, correctness, and retrieval quality - because a single aggregate score hides the failures that matter most in production.

  • Real benchmark data from 600 queries showing that provider differences don't surface on easy factual lookups - they emerge on the hard queries your system actually needs to get right.

If you're selecting a web search provider, optimizing a retrieval pipeline, or building AI agents that need to operate on live web data, this is the playbook for making that decision with evidence instead of intuition.

Download the guide