Kapitol.ai vs RazFit

Members of Congress trade stocks on insider knowledge - legally. Under the STOCK Act, they must disclose every trade, but those filings are buried in government databases and nearly impossible to act on.

Kapitol.ai fixes that. We monitor all 535 Congress members, collect every filing the moment it drops, and score each trade on committee jurisdiction, position size, and political timing. Only the highest-signal moves make it to your feed, with plain-English analysis explaining exactly why it matters.

Not every congressional trade is worth your attention. Ours are scored Low, Medium, High, or Critical based on how strong the insider signal is. Critical trades come from committee chairs with direct jurisdiction and maximum position size, historically the highest-conviction calls.

Free account included. No credit card required.

RazFit is a sophisticated, native iOS fitness application engineered exclusively with SwiftUI for iPhone and iPad, requiring iOS 18 or later. It is a comprehensive fitness solution designed to deliver measurable physical transformation through high-intensity, bodyweight interval training (HIIT) protocols condensed into 1 to 10-minute daily sessions. The core value proposition is maximum efficiency: it eliminates the need for gym access, specialized equipment, or significant time commitments. The application is architected for a broad user demographic, from fitness novices seeking an accessible entry point to advanced athletes requiring a time-efficient maintenance or conditioning tool. Its technical foundation in SwiftUI ensures a fluid, responsive, and deeply integrated user experience that leverages the full performance capabilities of modern iOS hardware. Central to its functionality is an adaptive AI coaching system featuring two virtual trainers, Orion and Lyss, which conduct initial fitness assessments and dynamically modulate exercise difficulty and selection. This is complemented by a structured gamification layer comprising 32 unlockable achievement milestones, engineered to sustain user engagement over a longitudinal 52-week training cycle. Every prescribed exercise includes scalable modifications, allowing for precise user-controlled progression.