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IdeaUnderservedWEB-APPSEARCHRESEARCHLive

A search engine that indexes agentic AI research papers, benchmarks, and safety evaluations so builders can ground their architecture decisions in peer-reviewed evidence

ACM just launched CAIS 2026, the first academic conference dedicated to agentic AI systems, with 63 papers and 46 demos covering multi-agent architecture, safety, and evaluation. Meanwhile academic security research like Prism is publishing formal verification approaches for agent runtimes. Builders making production architecture decisions (sandboxing strategy, multi-agent composition, tool-use safety) have no way to find relevant academic work without manually scanning arxiv and conference proceedings. This tool indexes agentic AI papers, extracts actionable findings, and surfaces them when a builder searches for their specific technical challenge.

Gap Assessment

UnderservedExisting solutions leave gaps. Underserved market

2 tools exist (Semantic Scholar, Papers With Code) but gaps remain: No agentic AI specific taxonomy, no extracted actionable findings for builders, no topic profile notifications; No focus on agentic AI architecture decisions, no builder-oriented finding extraction, no digest system.

Features3 agent-ready prompts

Crawler that indexes agentic AI papers from arxiv, ACM DL, and conference proceedings into a searchable vector store with extracted claims and findings
Search API that takes a builder technical question and returns ranked relevant papers with extracted actionable findings highlighted
Weekly digest generator that monitors new papers matching a builder saved topic profile and emails a summary of actionable findings

Competitive LandscapeFREE

ProductDoesMissing
Semantic ScholarGeneral academic paper search with AI-generated summaries across all fieldsNo agentic AI specific taxonomy, no extracted actionable findings for builders, no topic profile notifications
Papers With CodeLinks ML papers to their code implementations and benchmarksNo focus on agentic AI architecture decisions, no builder-oriented finding extraction, no digest system

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