Open-source Deep Research
Open-source Deep Research for Competitive Intelligence
Track competitors, positioning, adoption, and community reaction from cited public evidence.
01
Signals beyond company pages
Competitive intelligence needs more than websites and press releases. AutoSearch can gather GitHub activity, community complaints, launch discussions, video content, social posts, papers, and Chinese platform signals with citations.
02
Cited evidence improves debate
Competitor claims often become internal folklore. AutoSearch returns source-backed findings so teams can inspect adoption signals, pricing reactions, positioning shifts, and technical tradeoffs before making strategic decisions.
03
Multilingual market visibility
Competitors may be discussed differently across regions. AutoSearch includes 10+ Chinese sources, helping intelligence teams compare Chinese-language narratives with English developer and customer communities.
How it fits
AutoSearch fits into competitive intelligence as the source collection step for agents. A team can ask for a competitor brief, launch analysis, or category map. AutoSearch gathers cited public signals from 40 channels, then the agent structures the material into themes, gaps, and evidence tables. Human reviewers still judge relevance and confidence, but the source base is broader and easier to audit.
Try this prompt
Research how users compare AutoSearch, GPT Researcher, and Perplexica.
Use GitHub, Reddit, Hacker News, Twitter, YouTube, and Chinese sources with citations.