Nace AI releases Drex for Search for AI agents
MarkTechPost: Nace AI Releases Drex for Search for AI Agents: 92.05% on BrowseComp-Plus With 12.6 Search Calls
Nace AI has released Drex for Search, which brings its Drex decision models to document search. Drex for Search is a retrieval layer that helps people and agents find evidence. Coding agents such as Claude Code, Codex, Cursor and OpenCode call it through CLI, SDKs, MCP or REST. In Nace’s evaluation, it scores 92.05% on BrowseComp-Plus with GPT-5, using 12.6 search calls per question. TL;DR Size: a hosted search system built to search over 1M+ files. It pairs with an answering model
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Drex for Search is a retrieval system designed to help AI agents find information across documents by treating search as a series of decisions rather than simple keyword matching. The system narrows down results progressively through folders, files, sections, and pages to return cited sources instead of generic text chunks. In benchmark testing, it achieved 92.05% accuracy on one evaluation while using significantly fewer search calls than competing systems, and showed measurable improvements across multiple agent and model combinations by reducing the number of steps needed to find answers.
Explainer: Why Cursor Is Training Its Own Trillion-Parameter AI Model
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