Instruments
Built to do our own work.
Sold because they hold up.
Every one of these exists because we needed it for a question we were trying to answer. That ordering is why we can tell you where each of them stops.
Fluxus
ProductQubit and SFQ chip design, as a sub-second function instead of an hour in the solver. Buy either half, or both for co-design.
0.48%
median resonator error vs HFSS, grouped held-out split
Corpus
ProductDesign-rule checking where every rule carries how it was settled — and where the honest denominator is published alongside the count.
169
settled rules of 218 — 40 by our own exact simulation, 48 by a read theorem, 66 endorsed conventions, 15 traced to a cited source
Readout Co-Design
EngagementScoped engagements on reading protected qubits without wrecking the protection.
from $20k
fixed-scope deliverables, priced before we start
The problem we solve
Simulation doesn't scale.
Full-fidelity simulation is accurate but slow. A 1,000-cell RSFQ block takes 5–10 minutes in SPICE; a full chip is an engineering day, per iteration. The constraint isn't compute — it's the simulation paradigm itself.
How an engagement runs
01
Share your simulation data
Cell library and reference simulation outputs for your process node — MIT-LL SFQ5ee+, IPHT, SeeQC, AIST, SkyWater, or proprietary.
02
We train the surrogate
Calibrated to your junction parameters, cell geometry, and design rules. Training runs on your data.
03
Explore at ~10³×
Design-space exploration with per-cell confidence scoring. Low-sigma predictions pass; high-sigma cells are flagged.
04
Validate the shortlist
Your reference simulator validates the finalists. Every shipped design is ground-truth verified.
Access
Fluxus and Corpus are delivered as an API and CLI, trained per process node. Readout Co-Design is scoped and priced before any work starts. All three are calibrated to your process rather than sold as a general model.