Turn usernames into review-ready intelligence briefs - Autoresearch

Autoresearch turns a username into a review-ready intelligence brief. It searches public account signals across social, developer, creator, marketplace, and forum surfaces, then organizes matches into confidence notes, watchlists, exports, and team review workflows. Built for teams that need structured public username research instead of scattered manual searching.

Kilo Code v7 for VS Code — Run Parallel AI Agents in VS Code. Free & Open Source

Run Parallel AI Agents in VS Code. Free & Open Source

Hi everyone 👋 I built Autoresearch because username research is still surprisingly manual. When a team needs to understand a public handle, they often jump between social platforms, developer profiles, forums, marketplaces, creator pages, and spreadsheets — then struggle to package the findings into something another person can actually review. Autoresearch turns a username into a structured, review-ready intelligence brief. It helps you: - search public account signals across 400+ public sources - review username matches across platforms - check identity consistency and confidence signals - create watchlists and confidence notes - export findings for team review - support brand watch, impersonation risk review, and public account discovery workflows The goal is not to replace human judgment, but to make public-signal research easier to inspect, discuss, and act on. I’d love to hear your feedback, especially from teams that do research, trust & safety, brand monitoring, or public account review work.

Kilo Code v7 for VS Code — Run Parallel AI Agents in VS Code. Free & Open Source

Run Parallel AI Agents in VS Code. Free & Open Source