Open-source Deep Research
Open-source Deep Research for Finance
Collect cited market, technology, and public sentiment context for analyst workflows.
01
Public evidence for analyst notes
Finance teams often need context from filings, news, repositories, communities, and regional platforms. AutoSearch helps gather cited public evidence that analysts can review before forming market, technology, or competitive views.
02
Compliance review remains separate
AutoSearch is designed for source discovery, not trading advice. Its LLM-decoupled approach lets firms keep compliance checks, investment judgment, and restricted data policies in their own workflow while improving public research collection.
03
Chinese sources for market color
Chinese platforms can surface product adoption, consumer sentiment, and local competitor signals earlier than English sources. AutoSearch includes 10+ Chinese sources, allowing finance researchers to include multilingual public context with citations.
How it fits
AutoSearch works upstream of finance analysis as an MCP-native public research tool. An analyst or agent can request cited evidence across 40 channels, including technical communities, social platforms, news-like sources, and Chinese discussions. The output can support diligence notes, market maps, or technology trend research. Final analysis, compliance review, and investment decisions stay in the team's governed systems and human review process.
Try this prompt
Research public sentiment and developer adoption around agentic coding tools.
Compare GitHub, Reddit, Hacker News, Twitter, and Chinese sources with citations.