Bravon

Bravon — Reliability, Proven is a verification-first AI engineering platform developed for the Meta Global AI Developer Hackathon 2026. AI-generated repairs can pass visible tests while leaving critical behavioral or security requirements broken. Bravon addresses this problem by allowing Meta models to investigate failures through bounded, read-only tools, then independently testing proposed repairs inside isolated environments. Our hackathon work introduced structured Meta-model investigations, isolated repair verification, false-green rejection, evidence-backed reporting, and an experimental safety-rule transfer system called Immortality. Across nine recorded local Meta Llama 3.1 investigations, four repair proposals passed independent verification, two incomplete proposals were rejected, and three investigations ended in abstention. A separate operator-reported Meta Muse Spark 1.3 experiment investigated a real DNS fault in a disposable Docker environment. Bravon then tested a bounded DNS safety invariant on a second isolated system, blocking an unsafe change while allowing a legitimate one. The public product offers a read-only evidence experience. Results are limited to controlled experiments, and pre-existing foundations are separately disclosed. AI proposes. Independent evidence decides.