Open-source Deep Research

Open-source Deep Research for Journalism

Collect source-backed leads, background, and multilingual context before reporting begins.

Citations support editorial checks

Journalists need to trace every factual claim. AutoSearch returns cited public findings from multiple channels, helping reporters build background packets that editors can inspect before interviews, drafts, or publication decisions.

Community signals and documents

Stories often emerge from forums, repositories, academic work, social posts, videos, and regional platforms. AutoSearch helps agents collect those signals together, making it easier to spot contradictions, timelines, and source gaps.

Chinese coverage for global stories

Global technology and policy stories may have important Chinese-language context. AutoSearch includes 10+ Chinese sources, helping reporters compare narratives and public discussion across regions before framing a story.

How it fits

AutoSearch works as a public source discovery tool in a journalist's agent workflow. The reporter can ask for background across 40 channels, then use the cited output to plan interviews, verify timelines, or identify missing documents. It does not replace editorial judgment, direct confirmation, or newsroom standards. It gives reporters a faster way to assemble traceable context before deeper reporting begins.

Try this prompt

Research the public timeline of MCP adoption in coding tools.
Collect cited sources from docs, GitHub, forums, social posts, and Chinese platforms.