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feezify is a training copilot — not a coach. It helps you read your own day. Every morning (or whenever you ask), it looks at two things and crosses them:

Then it tells you, in plain language, whether today is green, amber, or red, and why. That’s it. You decide what to do with it.

What it does

What it does not do

This isn’t a limitation to route around — it’s the design. feezify makes you a better reader of your own body; it doesn’t outsource the judgment.

Where it came from

feezify used to be a hosted SaaS — a Node/Express/Mongo app with accounts, a database, a server, a frontend, deploys. Most of that was plumbing. The actual value was one small thing buried inside: a way of crossing objective training load with subjective readiness, and a judgment about when how-you-feel should override what-the-numbers-say.

When AI agents arrived, roughly 90% of that app became dead weight. The method didn’t. So feezify was rebuilt AI-native.

The AI-native remap

The old web app and the new agent map tier for tier. The browser was the last interface shift; the LLM/chatbot is the next one. You don’t plug the old app into it — you rebuild the engine one layer down, as an agent, and the database becomes a memory:

Classic web app The tier AI-native feezify
Browser / frontend the interface the LLM / the chatbot (Claude, OpenClaw…)
Server / backend the application engine the agent — a pure method core + adapters to third-party apps
Database the persistence a second-brain memory — your journal + the copilot’s own compiled memory of you

You don’t open feezify’s app. You install feezify’s agent on your own AI.

Who it’s for

Ready? → Install feezify