Product
Market intelligence, not another picks feed
Kam watches games, sportsbooks, prediction markets, schedules, and saved reads so users can see what moved, what is stale, and what to verify next.
About John Yu
I'm building Kam so bettors see the market before they fire.
I'm John Yu, founder of Kam AI. I build the product, systems, writing, and workflows behind Kam. The idea is simple: pick your spots, let Kam read the market shape, and get a clear read before you act.
Engineering
Web, mobile, backend, data, and AI in one loop
The work spans Next.js, React Native, backend APIs, source checks, admin review, evals, saved reads, and chat.
Taste
Simple words beat systems theater
Users should know what changed, what is stale, what is missing, and what to check before they act.
What Kam stands for
A better bet starts before the bet.
Catch moves. Don't chase.
Kam should help users see the market shape before they take a worse number.
No fake locks.
The product should never promise winners, sure things, or risk-free bets.
Show the missing info.
If sportsbook, prediction-market, schedule, or injury context is stale or missing, say it clearly.
Keep the final call human.
Kam can organize the read. The user owns the bet, wait, pass, and review.
What is already built
Kam is more than a landing page.
A Next.js public layer with product pages, Fumadocs docs, blog, and protected admin surfaces.
A React Native product direction for sports-market research and AI chat workflows.
Backend proxy and admin auth flows that protect operational tools with Cognito and Google Workspace.
Manual Data Ops tools for staged batches, validation, review, import, rollback, and audit history.
A docs and writing system that explains Kam in plain English instead of hype.
Assistant rules so Kam sounds like a market-intelligence layer, not a generic chatbot.