Open-source Deep Research

Open-source Deep Research for Legal Research

Collect source-backed legal context for memos, market scans, and policy questions.

Citations support review workflows

Legal research needs inspectable provenance. AutoSearch returns cited findings so attorneys, analysts, or policy teams can trace claims back to source material before using them in memos, client notes, or internal decision records.

Coverage beyond legal databases

Many legal questions involve industry behavior, public commentary, enforcement trends, and technical facts. AutoSearch can gather from news, repositories, forums, papers, social channels, and Chinese sources to broaden context around formal legal research.

Compliance boundaries stay visible

AutoSearch is best used for source discovery and context gathering, not legal advice. Its LLM-decoupled design lets firms keep review, privilege controls, and final interpretation in their own systems while still improving evidence collection.

How it fits

AutoSearch sits upstream of legal analysis as an MCP-native research tool. A legal team can ask an agent to collect public evidence across 40 channels, including regulatory commentary, technical discussions, market examples, and Chinese-language sources. The agent receives cited findings and can draft a research brief, but human review remains responsible for legal interpretation, confidentiality, and client-specific judgment. This makes AutoSearch useful for preliminary context, not a substitute for counsel.

Try this prompt

Research public discussion and technical context around AI agent liability.
Collect cited sources from policy, news, GitHub, and academic channels.