Overview
AskCyborg helps investors, founders, analysts, operators, and other professionals decide whether a company is a go or no-go. Instead of presenting another database of raw facts, it organizes complex research into an actionable intelligence package.
The experience follows a progressive path: discover a company, review its central thesis and Cyborg Score, hear a bull-versus-bear analyst debate, read the complete strategic report, explore competitor and industry context, and save the company for ongoing monitoring.
The product is designed to communicate a conclusion quickly without presenting AI analysis as unquestionable. Scores are paired with human-readable theses, competing perspectives, caveats, recorded dates, methodology information, and deeper supporting material.
Different research modes serve different contexts. Users can scan company cards, read long-form reports, listen to analyst debates and industry playlists, or follow watchlist briefings when reading is inconvenient.
Public performance metrics were not supplied, so this case study describes the live delivered experience without making unsupported conversion, subscription, coverage, or business-result claims.
What I built
- Designed a decision-first product hierarchy around company search, the Cyborg Score, concise company theses, and analyst debates.
- Created reusable discovery patterns for public companies, private companies, industries, IPO watchlists, and thematic collections.
- Designed progressive research journeys spanning fast summaries, complete reports, audio debates, competitor playlists, and watchlist briefings.
- Developed the responsive web product experience represented in the supplied project brief.
Highlights
- Decision-first 1–10 Cyborg Score and company thesis
- Bull-versus-bear analyst debates and long-form reports
- Company, competitor, industry, and watchlist research flows
- Progressive disclosure for casual and professional users
- Live freemium research product