Measuring Search API Latency for Real-Time Agent Loops
Cumulative latency across sequential searches matters more than any single API call's speed.
Cumulative latency across sequential searches matters more than any single API call's speed.
A benchmark for financial AI that tests retrieval over reasoning in open-domain search.
New benchmark measures whether AI can find every correct answer, not just one.
Reranking filters noise from initial search results to deliver cleaner context for language models.
How you split web documents for LLMs shapes every retrieval decision that follows.
Hybrid retrieval fixes blind spots no single search method can overcome.
Integrating live web APIs into language models keeps them current and cuts hallucination risks.
Test RAG systems at three separate layers, not one end-to-end score.
Prompt design, not model capacity, determines whether retrieved facts actually ground LLM answers.
Stream search results into models without blocking retrieval or losing performance to buffering.
Grounding LLM answers in retrieved facts eliminates the model's need to fabricate from memory.
Agents fail on live websites because they can't see what humans see.