Q1 2026 GA · $40,000 · 2-week delivery

The Quantum Audit.

Find quantum-acceleratable workloads in your classical clusters. Two weeks. One report. Zero vaporware.

The problem we are paid to solve.

Your Fortune 500 engineering team runs tens of thousands of jobs every month on classical HPC. Some of them bleed millions. Some will benefit from quantum acceleration when the hardware matures.

Nobody can tell you which. That is the audit.

Process

Two weeks. Four steps. One report.

1
Day 1–3

Kickoff & Scope

Mutual NDA. Scoping call. We provide the on-prem CLI binary + Docker image. Your team confirms which Slurm / K8s / PBS clusters are in scope.

2
Day 4–10

On-Prem Audit

CLI runs inside your firewall against scheduler logs. No raw data leaves your network. Classification + QSS + cost analysis happens locally on the head node.

3
Day 11–13

Report Drafting

PDF generated locally. Technical advisor reviews the methodology and signs the final report. You see and approve the sanitized Latency Index manifest before any data crosses the firewall.

4
Day 14

Delivery & Debrief

Board-ready PDF delivered. 2-hour debrief call with your engineering team. Top 10 workloads ranked. Next-quarter recommendations.

The IP

The 15 archetypes.

Every workload in your audit is classified against this library. Each archetype carries a hardware horizon and a confidence band — both visible to you in the final report.

Optimization

Combinatorial QAOA

medium

Max-Cut / MIS / scheduling

Horizon: 2028

Portfolio QAOA

high

Allocation with budget + risk constraints

Horizon: 2028

MILP-mapped routing

medium

Vehicle routing / network flow

Horizon: 2030+

Simulation

VQE molecular Hamiltonian

high

Drug discovery, small-molecule energetics

Horizon: 2026

Quantum chemistry

high

Electronic structure beyond DFT

Horizon: 2028

QPE eigenvalue

medium

High-precision spectral problems

Horizon: 2030+

Search

Grover unstructured

low

Pre-image / SAT search

Horizon: 2030+

Grover-mapped CSP

low

Constraint satisfaction

Horizon: 2030+

Linear Algebra

HHL

low

Sparse linear systems (caveats apply)

Horizon: 2030+

Amplitude Estimation

medium

Monte Carlo / derivatives / risk

Horizon: 2028

Number Theory

Shor's algorithm

speculative

Factoring / discrete log

Horizon: speculative

ML / Hybrid

Quantum kernel methods

low

SVM / classification on quantum features

Horizon: 2028

Variational gradient

speculative

Quantum-assisted training

Horizon: speculative

Graph / Stochastic

Quantum walks

low

Graph traversal / centrality

Horizon: 2030+

Stochastic optimization

medium

Optimization under uncertainty

Horizon: 2028

What this engagement actually buys you.

Three columns. The third column is the moat.

What we measure

  • Every job classified against the 15-archetype library with high / medium / low / speculative confidence
  • QSS computed per workload — five inputs, five weights, fully auditable
  • Dollar-cost of every bottleneck using your supplied compute rates and observed runtime
  • Earliest credible hardware horizon per archetype, with cited literature
  • Queue-wait amortization across the top 10 workloads

What we deliver

  • Board-ready PDF — executive summary, workload inventory, top 10 bottlenecks, QSS per workload, methodology appendix
  • Methodology hash on every page — version-pinned to the public methodology PDF
  • Anonymized Latency Index ranking — where you sit against industry peers (banded, not named)
  • Prioritized roadmap of the workloads to track on each new QPU generation
  • Two-hour debrief call with your engineering team

What we won't claim

  • Specific speedup multipliers on today's NISQ-era hardware
  • Quantum-advantage delivery dates we cannot defend with published evidence
  • Vendor performance comparisons (IBM vs. IonQ vs. neutral-atom vs. anyone)
  • ROI projections beyond classical bottleneck cost on your own infrastructure
  • Forced classifications when no archetype credibly fits

This is the page no consultant writes. It is the page Fortune 500 CTOs pay for.

FICO for Quantum

The Quantum Suitability Score, in practice.

Three real-shaped sample workloads, the same five inputs, three different verdicts.

87
High

VQE-mappable molecular dynamics (drug discovery)

Archetype Match28/30
Problem Size17/20
Classical Cost22/25
Hardware Horizon12/15
Translation Difficulty8/10

Design-partner candidate when fault-tolerant chemistry hardware ships in stated horizon.

62
Medium

Monte Carlo derivatives pricing (overnight risk)

Archetype Match21/30
Problem Size14/20
Classical Cost18/25
Hardware Horizon6/15
Translation Difficulty3/10

Track quarterly. Amplitude estimation has known speedup but requires hardware not yet at production fidelity.

12
Not a candidate

Customer churn ML pipeline (gradient boosting on tabular data)

Archetype Match4/30
Problem Size3/20
Classical Cost3/25
Hardware Horizon1/15
Translation Difficulty1/10

Classical is the right answer. No reasonable QPU horizon delivers value here. We will tell you this in writing.

Sample scores are illustrative. Real scores are computed deterministically from your scheduler logs, your compute rates, and the public methodology — and are reproducible from the inputs.

Security

Runs inside your firewall. Period.

The audit CLI is a single signed binary. It runs on your HPC head node. It reads scheduler logs and process metadata locally. It never opens an outbound connection unless you type the consent flag.

Even then, the only data that leaves your network is the sanitized JSON manifest you reviewed yourself — hashed job names, archetype counters, aggregate cost vectors, scheduler type. No raw logs. No file paths. No user IDs. No source code.

On-prem only — single binary (PyInstaller) or Docker
Air-gapped environments supported
Sanitization layer — hashed names, no paths, no PII
Customer-typed consent flag before any manifest export
Mutual NDA on every engagement
Sample

What lands on your desk on Day 14.

A board-ready PDF. Methodology hash on every page. Signed by the technical advisor on file.

Executive Summary
2 pages
#methodology-v1.0.0
Workload Inventory
Top 50 jobs
#methodology-v1.0.0
Top 10 Bottlenecks
$/year cost
#methodology-v1.0.0
QSS per Workload
Auditable scores
#methodology-v1.0.0
Pricing

One SKU. Forty thousand dollars.

Single SKU for the first ten engagements. Tiered pricing after.

Quantum Audit
$40,000
per engagement · two-week delivery
Q1 GA

Included

  • CLI license + on-prem deployment support
  • Advisor-reviewed PDF report
  • Anonymized Latency Index ranking
  • Two-hour debrief call
  • Signed methodology PDF

Not included

  • Ongoing monitoring (Q3 2026 scheduler product)
  • Pilot implementation work (separate SOW)
  • Custom archetype development (case-by-case)
  • LSF support in v1

Questions we always get.

Do you support LSF in v1?+
No. Slurm, Kubernetes (stock + Argo Workflows), and PBS Pro only. LSF is v1.1, post the first 5 paid audits. If LSF is a hard requirement, tell us during scoping — we will quote a custom engagement.
Will you sign a mutual NDA?+
Yes. Mutual NDA is a precondition of every engagement. We provide our template; we accept yours with reasonable redlines.
Can the audit run without your team on site?+
Yes. The CLI is single-binary (PyInstaller) or Docker image. Your team runs it. We are available on a video bridge for the kickoff call, the consent review before any manifest upload, and the final debrief.
Do you make claims about specific QPU vendors?+
No. We classify workloads against published quantum-advantaged problem archetypes. We do not project relative performance of IBM vs. IonQ vs. neutral-atom vs. anyone. The honesty guardrail prohibits it and our methodology PDF documents it.
What if our workload does not match any archetype?+
We report it honestly as "no quantum candidate" and explain why. There is no upcharge and the audit price does not change. The Latency Index value comes from the full inventory, not from forcing every workload into a category.
Is the methodology public?+
Yes. The methodology PDF is published at /methodology and signed by our technical advisor. Every quantitative claim in your report cites an entry in the methodology appendix. Every report carries a methodology hash on the last page so future versions can be tracked.
Who is the technical advisor?+
Named on /methodology and on your engagement SOW. The advisor reviews and signs every report. If we cannot name a credible advisor for your industry vertical, we will not take the engagement.
Will you share our results with other customers?+
Only the sanitized, customer-approved JSON manifest is uploaded to Q-Intercept, and only after you review and approve it via the CLI consent flag. Aggregate counts feed the Latency Index. No customer is ever named. No raw job data, paths, or user IDs leave your network.

Ready to know which workloads quantum will actually help?

Book a thirty-minute discovery call. We will scope your engagement and send a SOW within 48 hours.