Research Agent
An AI agent that autonomously searches the web, reads documents, synthesizes findings, and produces cited reports by iteratively formulating queries and evaluating retrieved information against a research goal.
Research agents combine web search, document retrieval, and synthesis in a loop. A common pattern is: decompose the research question into sub-queries, retrieve and read sources in parallel, score sources for relevance and credibility, then synthesize a draft with inline citations. The agent iterates until coverage of the question reaches a confidence threshold.
Quality controls include source diversity (avoiding echo-chamber retrieval), recency filtering, and factual cross-validation across multiple sources. Research agents are particularly prone to hallucination when sources conflict, so strong implementations explicitly represent uncertainty and surface disagreements rather than smoothing them over.
Production research agents in 2026 typically use a fast, cheap model (e.g., Grok 4.1 Fast or Gemini 2.5 Flash) for initial retrieval and a stronger model (Sonnet 4.6 or Opus 4.7) for synthesis and fact-checking. This mix balances cost and quality effectively.