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Web Retrieval Agent is an AI agent that takes a plain-English question, searches the live web, reads the actual pages and returns only the specific information the user asked for, together with the exact quote that proves it. Most AI search tools write a fluent answer and ask you to trust it. This agent treats the language model as untrusted. It plans targeted search queries, uses Tavily to search and extract full page text, and asks the LLM (gpt-oss-120b on Groq) for a structured answer with verbatim evidence quotes. The server then checks every quote against the real page text and drops any that do not appear. If the answer contains a figure that the quotes do not support, confidence is lowered and the user is warned. If the sources do not contain the answer, the agent says so instead of guessing, and it can retry once with refined queries focused on a likely site. The interface streams the agent's activity live (planning, searching, reading, verifying), then shows the answer, a confidence meter, the proof quotes with source links and every source checked. It is built with Next.js and TypeScript and deployed on Vercel. The LLM client works with any OpenAI-compatible endpoint, so the model can be swapped for an open model served on AMD GPUs.

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