Museance

The problem - Supermarket cold rooms run on old controllers that accept unauthenticated commands. In the Oct/Nov 2026 EU attacks, a single remote write could switch off cooling and silence the alarm. - Rebuilding that legacy software is risky: an AI can rewrite it fast, but nobody can prove the rewrite keeps the food cold. What MUSÉANCE does - AI proposes, the court decides. An AI rebuilds and patches the controller, and swears how every behavior works, with credits on the line. - A court with no AI tests both builds side by side over Modbus TCP, the controller's own industrial protocol, and runs every check twice. - Every verdict goes into a hash-chained ledger. Only behaviors that survive the court get locked into the record. Proof it works (measured today) - Cooling on and off, temperature hysteresis, the high-temperature alarm and the defrost schedule: 6/6 behaviors identical on both builds, all locked, zero flaky. - 3/3 unauthorized configuration changes: the legacy controller accepted every one, and the patched build rejected all three, kept troom at 4 °C and its alarm working. - The patch is three lines. The ledger holds 24 events with the chain intact. The same court also scored a revived 2016 todo app fro41% to 100% faithful. ilt with - Fetch.ai agents argue the case live in ASI:One. SubQ scores each claim's confidence. MongoDB's AI finds the evidence behind every claim. Codex and Meta Muse rebuild. Our mission - Make AI fixes to critical infrastructure accountable: every claim is staked, every verdict comes from a test, and nothing ships unproven. Modeled controller, not vendor code.