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Axiomo

Axiomo

PR intent and context signals, not AI code review noise

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Most AI code review tools flood your PRs with line-level nitpicks. Axiomo takes a different approach. It surfaces the signal that actually matters before you review. For every PR, Axiomo generates a structured Signal: contributor context, intent summary, risk drivers, CI evidence, and focus files. You see who's changing what, why it matters, and where to look first. No auto-generated code suggestions. No comment spam. Just the context you need to review PRs with confidence instead of fatigue.
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Launch tags:Developer Tools•Artificial Intelligence•GitHub
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Framer
Framer
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kxbnb
Maker
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Hey everyone, I built Axiomo because AI code review tools kept solving the wrong problem for me. They all want to be a second developer on your PR. Catching lint issues, suggesting refactors, rewriting your code. That stuff is fine but it's not what makes PR review hard. What makes it hard is context. Who wrote this? Have they touched this area before? What are they actually trying to do? What's risky here and where should I focus? Axiomo generates what I call a Signal for every PR. It's a structured breakdown of contributor context, intent, risk drivers, CI evidence, and the specific files you should pay attention to. It doesn't tell you what to change. It tells you where to look and why. I've been reviewing PRs for a long time across teams of different sizes and the pattern is always the same. You open a big diff, you skim, you approve, and you hope nothing breaks. I wanted something that actually helped me review instead of just adding more noise to the PR. Would love to hear what your review process looks like and what part of it feels broken to you.