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

Product

Qubit 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

Product

Design-rule checking where every rule carries how it was settled — and where the honest denominator is published alongside the count.

170

settled rules of 219 — 40 by our own exact simulation, 48 by a read theorem, 67 endorsed conventions, 15 traced to a cited source

Readout Co-Design

Engagement

Scoped engagements on reading protected qubits without wrecking the protection.

from $30k

fixed-scope deliverables, priced before we start

The problem we solve

Simulation doesn't scale.

Full-fidelity simulation is accurate but slow. One RSFQ margin characterization takes about 3.78 s in JoSIM, so a sweep of 1,000 specs is about an hour, per iteration. The constraint isn't compute — it's the simulation paradigm itself.

Speed

Sequential. 3.78 s per JoSIM margin run; about an hour per 1,000 specs.

Batch-parallel. 1,000 specs in about 43 ms.

Confidence

One answer. No uncertainty. No ranking.

90% split-conformal bands on served margins. Ambiguous cases defer to JoSIM.

Scale

Every candidate requires full simulation.

Screen 10,000 candidates. SPICE validates the shortlist.

Refusal

Answers any netlist it can parse, in range or not.

Refuses outside the envelope it was measured on, and names the field.

How an engagement runs

Share your simulation data

Cell library and reference simulation outputs for your process node. Fluxus is retargeted from your reference simulator; the process records built in today are MIT-LL SFQ5ee-style and AIST-style literature anchors, not validated PDK data.

We train the surrogate

Calibrated to your junction parameters, cell geometry, and design rules. Training runs on your data.

Sweep 1,000 specs in ~43 ms

Design-space exploration with per-cell confidence scoring, batched. Calibrated predictions answer; ambiguous ones are handed back to the exact solver.

Validate the shortlist

Your reference simulator validates the finalists before anything is committed. The surrogate narrows the search; it does not sign off a design.

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.

Talk to us Or get API access →

Built to do our own work.Sold because they hold up.