Quantum-Optimised Routing & Assurance
Every safety-critical system is designed against one rule: no single failure may lead to a catastrophic event. Electrification is making that rule harder to hold, and single-failure thinking is no longer enough. QORA's engineering software routes every signal at once as one global solve, sweeps combinations of failures against the result, and has an independent verifier prove every rule before a design is accepted. Aircraft first, then any system whose signals must survive.
Every safety-critical system is designed against one rule: no single failure may lead to a catastrophic event. Engineers hold that line system by system, against rules written by the certification authorities and by their own company. Electrification is changing what holding it takes. High voltage now runs through the same hull as safety-critical signals, beside next-generation batteries and hydrogen fuel systems, in an airliner that already carries over 100 km of wiring.
Electric propulsion brings high-voltage power into airframes built around signals that must never fail. Next-generation batteries and fuel systems add new hazard zones, and each one constrains where every wire may run.
One catastrophic event is unaffordable; with human lives at stake, it is beyond price. That is why certification rules are hard constraints: never traded, never approximated, never assumed away.
More stored energy and more powered paths mean a single event, an uncontained rotor failure or a fire, can take out several channels at once. Particular risk analysis now has to cover combinations of failures, while routing can still change, not as a report on a design already frozen.
Our answer
Take in both rule books, solve routing as one problem, and prove the answer. QORA compiles the authorities' rules and the customer's own standards into one machine-readable set, routes every signal against them in a single global solve, sweeps failure combinations across the result, and feeds what it finds back into the next design update for a human to approve. Built quantum-ready for the scale that is coming. The rest of this page shows how.
QORA decides where every signal runs, all of them together as one optimization, then proves each safety rule holds, stress-tests the design against damage, and re-optimizes in seconds at demo scale when the design changes.
Signals are routed together, as one constrained optimization. Safety rules couple them pairwise, so sequential routing strands signals in our benchmarks that a global solve routes cleanly. Double-digit cost improvements over strong sequential baselines on synthetic instances, and every run reports how close to provably optimal it is.
Rules are machine-readable and carry their citations, whether they come from an authority document or a customer's internal standard. Solver output is proposed, never certified: an independent verifier re-derives every hard-rule check from raw geometry before any result is persisted. Audit reports regenerate byte-identical from archived runs.
Particular risk sweeps fly combinations of simultaneous damage scenarios against the routed design, multiple failures at once rather than one at a time, exactly what modern risk analysis demands. Every defeated redundancy group is found, fixed, and the re-sweep proves zero defeats: survivability tested, not assumed.
Move equipment, change a rule: a scoped re-solve freezes what can stay, reroutes what must move, names exactly which frozen routes conflict when the change over-constrains, and fully revalidates. Seconds, not days at demo scale.
The engine above wins at demo scale. Full-vehicle scale is a different problem, a load traditional computation was not built to carry. Safety rules couple signals to each other, pairwise, across the whole hull, so each signal's best path depends on every other signal's, and every failure combination added on top multiplies the work again. Measured on our own synthetic instances:
No human routes this by hand, and when a design truly is impossible, QORA names the exact signals that make it so. Past a few hundred signals, classical solvers increasingly lean on warm starts and decomposition to keep moving. This is precisely the problem shape annealing-based hybrid quantum solvers accept natively, hard constraints as constraints, never tuned into penalties, which is why the quantum adapter is built, tested and benchmarked before the scale arrives.
Position
Classical solving wins at today's scale, and our own benchmark says so. The product ships on classical optimization. Alongside it runs a native constrained-quadratic-model adapter, with an offline annealing path and a cloud hybrid backend, every sample held to the same proof standard as the classical path, every archived result replayable. Quantum is the measured scaling curve toward full-vehicle problem sizes, not the survival condition.
Agents propose · humans approve · the independent verifier gates everything
A certification document or a company standard goes in; machine-readable draft rules come out, each carrying a quote that must appear verbatim in the cited clause, so hallucinations die at the gate. Nothing becomes active without human approval.
When a damage sweep defeats a redundancy group, the agent drafts a new survivability rule carrying full provenance: which damage case, which routes, why. A human approves, the design re-solves, and the re-sweep proves the defeat is gone.
Routing evidence drives the next design move: agents read the verified result, draft the change, and hand it to the scoped re-solve to price, so the design keeps improving and only verified designs persist.
Aircraft first, with wiring governed by 14 CFR 25.1707-class certification rules. The model underneath is domain-agnostic: zones, bundles, redundancy groups, damage cases, citations. A new domain, or a customer's own internal standard, is another rule pack rather than another engine. The same engine routes: