Product · 1 min read
Why our first product never sees your code
Afara's backend never receives your source. The architecture choices behind local analysis, and what we gave up to get there.
Radicand Labs, Afara team
The first question every security team asks about an AI developer tool is some version of “where does our code go?” For Afara, we wanted the answer to be short: it doesn’t.
Commits, not the working tree
Afara reads commits, never your working tree. Uncommitted changes are never read or transmitted. That makes the input well defined and keeps half-finished work private by construction.
Your AI tool, on your machine
Afara doesn’t call a model of ours with your code. It runs the AI coding tool you already use and already trust, on your machine, under whatever agreement you already have with that provider. What comes back is a wireframe: nodes, edges and references to file paths. That graph is all that’s published.
What it cost us
Running analysis locally means we can’t batch work across customers or tune a single hosted model, and speed depends on the tool you have installed. We think that’s the right trade, and it’s a principle every Radicand Labs product will follow.