What is a Quantum Mesh Network?

An AI‑driven routing layer that load‑balances across the providers we route to today, optimizes cost and latency, and automates failover.

How does NL→Quantum work?

Our compiler converts plain‑English goals into optimized circuits in under 500ms with validation and provider selection.

How are costs reduced?

Provider arbitrage routes each run to the cheapest machine that meets its fidelity and latency constraints, with auditable quotes.

Introducing Hardware Pre-Flight: Validate Before Fabrication

QuantufAI Labs · 2025-01-15

Fabricating a quantum chip is a slow, expensive way to find out whether a design works. Hardware Pre-Flight exists to move as much of that discovery as possible in front of tape-out, where a design change is an edit rather than a new fabrication run.

What Pre-Flight does

Pre-Flight builds a digital twin of a proposed quantum processor — a simulation model of its physical characteristics and constraints — and runs decoder-aware tests against it. Decoder-in-the-loop matters because a qubit layout that looks fine in isolation can behave very differently once error correction is running on top of it: the decoder's per-round behavior is part of the system, not an afterthought.

The output is a Test Card: an auditable report covering threshold maps, predicted error rates, and throughput metrics for the design as simulated. "Auditable" is the operative word — every figure on a Test Card is traceable to the simulation that produced it, so a go/no-go decision can be interrogated rather than taken on faith.

What Pre-Flight does not claim

These are simulation results, and we label them that way. A digital twin predicts how a design should behave under the modeled physics; it does not certify how fabricated silicon will behave in a dilution refrigerator. The value is in ordering and filtering: designs that fail in simulation can be revised before anyone pays for a mask, and designs that pass arrive at fabrication with a documented, testable set of expectations.

We deliberately do not attach dollar or schedule savings to that. What a Test Card saves depends entirely on what it catches, and that is different for every design.

Where it fits in the platform

Pre-Flight sits at the front of the same pipeline as the rest of the platform: validate a design against its twin, then — once hardware exists — track how the real device's calibration telemetry compares with what the twin predicted. That closing of the loop between predicted and observed behavior is the long-term point of doing pre-flight validation at all.

Test Card figures are simulation predictions, not measured hardware results.

— QuantufAI Labs