Open-source Deep Research

Open-source Deep Research for Policy Research

Gather traceable policy context across papers, communities, technology sources, and regions.

Technical and social context together

Policy research often crosses law, technology, markets, and public behavior. AutoSearch can collect papers, GitHub discussions, community commentary, social posts, videos, and Chinese-language sources for a fuller evidence base.

Citations support public accountability

Policy teams need claims that can be checked by reviewers, stakeholders, and the public. AutoSearch returns cited findings, helping researchers preserve the source trail behind background notes and draft recommendations.

Good boundary for regulated work

AutoSearch collects public evidence and leaves interpretation, legal analysis, and institutional review to the policy team. That boundary is useful for compliance-sensitive topics where source gathering and final recommendations must be separated.

How it fits

AutoSearch sits in the evidence collection stage of policy research. An agent can ask it to scan public channels for a technology, regulation, or social issue. AutoSearch returns cited material from 40 channels, including academic and Chinese sources, which researchers can evaluate, annotate, and turn into briefs. It supports discovery and traceability while leaving judgment and institutional review with humans.

Try this prompt

Research current public debate about AI agents and data access policy.
Collect cited views from papers, GitHub, forums, news-like sources, and Chinese platforms.