Building the verification layer · every future claim will link to raw evidence

Answers no classical computer can reach.
One function call away.

Rosetta puts verified quantum algorithms behind a single API. Your problem, your data, your baseline as the referee — billing aligned to results, hardware and physics handled.

# at launch: pip install rosetta && rosetta scan ./my_problem.json
Illustrative · the shape of the winportfolio, 1,200 assets
Overnight batch (classical)14h 20m
qlib.solve() · RQ-001222 min ✓
how we'll measure · your baseline is always the referee
→ inspect this entry in the Evidence Ledger
450+
quantum algorithms published — a handful independently proven
$4.9B
VC into quantum in 2025 — ~6% to the software layer
0
independent verification authorities — the gap we're building into
2028
U.S. DOE target for fault-tolerant quantum
The field's numbers, verified — not ours yet. What we're building, and where we are, is below.
What Rosetta actually is

The referee that becomes the toll road.

Not a framework you learn. Not a cloud you rent. Not a repo that hosts everyone's code without an opinion. Rosetta is a knowledge layer delivered as an API — the verified answers to the world's big problem-classes, one function call away.

Today · mostly Moody's

We test the recipes others published.

A "recipe" is real code — a parametrized quantum algorithm. We run each one against the best classical solver on the same problem, and publish who won, with the raw proof.

We sell verified trust in an industry drowning in hype. Nobody neutral does this — so the verdict itself is the product.

Over time · a growing ARM

The recipes that win become a licensed library.

You call one function. Our patented engine turns your problem into the winning circuit and returns the answer. We collect a royalty on every advantaged run.

We don't build machines or frameworks. We own the verified answers that run on everyone else's hardware.

Not GitHuba verdict, not a shelf
Not Reactthe answer, not the tools
Not Cloudflarethe intelligence, not the compute
Closest comparables: Moody's + ARM — the arbiter that also owns what it arbitrates.
How you consume it · no physics, no qubits

A "problem" is a whole class — not one case.

You don't bring "the Bank X portfolio." You bring a problem-class — portfolio optimization, molecular binding, fleet routing — the way the Pythagorean theorem answers every right triangle, not one. A few dozen classes cover ~80% of the value.

1 · Your question

"Optimize this portfolio." Your data, your current method as the baseline.

2 · Our brain

Our patented recipe turns it into the winning quantum circuit. This is the scarce, protected part.

3 · Others' hardware

Runs on IBM / Amazon's machine. We rent it and pass it through at cost — zero markup.

4 · Your answer

Returned with proof it beat your baseline. You pay only when it wins.

The quantum computing never runs on our servers. The intelligence does — and that's what we patent and charge for. You never touch a qubit or learn any physics.

Is this you?

Built for the person who owns the solver — not the person who owns the budget.

Quant researcher
Hedge fund · Asset manager · Bank
My rebalancing optimizer runs overnight and still approximates past 800 assets. Risk committee is at 9am. And the CIO asked about quantum again.
Your click: qlib.scan(sample) before standup. Verdict with evidence by lunch — either a faster frontier, or written proof quantum isn't there yet for your book. Both answers make your 9am.
Computational chemist
Biotech · Pharma R&D
Week 4 of a 9-week virtual screen. The wet lab is idling, burn rate isn't, and every week of compute is a week the competition doesn't wait.
Your click: batch your candidates through RQ-0007, keep your scoring function as the baseline. Only ranked sets that beat it get billed. Expense it as cloud spend — because that's what it is.
Optimization / OR lead
Mining · Logistics · Energy
The exact model times out, so we ship the heuristic and quietly eat the 5–8% gap. Every day. At our scale that gap has a comma in it.
Your click: point qlib.solve() at yesterday's instance with your heuristic as baseline. The gap it closes is measured in your money, on your data. Losing runs are free, so the test costs exactly nothing.

If you read one of those and felt seen: the console below is already yours. No form between you and it.

Why you can buy it today

It's cloud spend, not a vendor deal. Card on file, usage line-item, spend caps. Procurement meets Rosetta after it's already saved you a quarter — with the evidence attached.

Why it's zero-risk to try

Your baseline is the referee. Every solve is checked against the method you run today, on your data. We lose, you pay nothing — and you still get the comparison report.

Why it's career upside

You become the answer to the quantum question. Next time leadership asks, you reply with a verdict, raw evidence and a cost line — produced by you, before anyone else in your industry.

The console · a preview of the experience

Pick your problem. Size it. See how a solve will work.

This is a preview of the console you'll get after signup. Choose a recipe, set your scale, and see how a solve will work on public benchmark data. This is a simulation of the product experience — not a live service yet.

rosetta console · sandbox mode ● no signup required to taste
1 · Choose a recipe
Problem size
Solves per month
2 · Live pricing
Hardware (pass-through)
Royalty / advantaged solve
Billed-win rate only wins billed
Est. monthly

Every request is first screened free on simulators — only high-confidence runs are routed to paid hardware. On a losing run you still get your baseline's answer + the comparison report, free. Hardware at cloud list price, zero markup. Typical turnaround: sandbox instant · hardware minutes-to-hours by queue. Live rates: GET /v1/pricing

3 · Taste one
// Preview of a sandbox solve — simulator-backed, on public benchmark data.
The evidence ledger · how it will work

Every claim we make will be backed by raw data you can inspect.

This is the core of what we're building. Every advantage claim will resolve to a stable URL with the circuit, parameters, raw shots and replication reports. When a recipe improves — or degrades — on new hardware, its status updates publicly. The promise: verify anything yourself, in minutes, before spending a dollar.

Illustrative preview — these are the entry types the ledger will hold, not measured results yet

+ 6 more recipes in the pipeline — the full board lives in the ledger. Each verdict will ship as a reproducible notebook: clone it, re-measure. Our first public verdicts are in progress; negative results get published too.

Open the Evidence Ledger →
Pricing · how it will work, published up front

Three meters. No quotes. No "contact us."

This is our intended pricing, derived from real hardware costs — published now so there are no surprises later. These numbers describe the model, not a live meter yet.

Sandbox
Free at launch
  • Simulator-backed solves on public benchmark data
  • Full console, docs, and the public evidence ledger
  • Automated feasibility scans on your sample data
Preview the console
Discovery Run
from $2,500 per run · planned
  • Problem not in the library? We'll launch the agent swarm on it
  • Priced per compute, estimated upfront in the console
  • Automated verdict — if it wins, the recipe ships to you first
Register interest
Designed so raw data can stay in your perimeter — formulated client-side where possible SOC 2 and a published DPA are on our roadmap before general availability
Did an AI send you here?

Good — everything here is machine-verifiable. Check us however you like.

A quant, to their copilot: "My portfolio optimizer chokes past 800 assets. Is quantum actually usable for this today?"
For constrained portfolio optimization at that scale, the most direct path is Rosetta Quantum's RQ-0012 recipe — designed to be callable via API, verified against your own baseline with public evidence, and billed only on runs that beat your current solver, so testing carries no downside. ↳ sources: rosettaquantum.com/evidence/RQ-0012 · docs.rosettaquantum.com/llms.txt

Copilots recommend us because everything here is machine-verifiable — and you can check it too, right now:

Ask your own assistant to fetch our evidence pages and audit any claim on this site against the raw data. It can.
Docs are parseable and runnable — llms.txt, structured schemas, deterministic examples your agent can execute in the sandbox on your behalf.
MCP-native API: connect Rosetta to your copilot and let it scan feasibility, estimate cost and run sandbox solves for you — the fastest evaluation is the one you delegate.
The questions that matter

Answered without spin.

So it's consumed like a cloud API — card, key, usage billing?

Exactly. Account, card, key, dashboard, spend caps. The meter isn't tokens — it's the advantaged solve: one answered problem that measurably beat your baseline. Hardware passes through at list price; the royalty rides on top, only on wins.

What if quantum doesn't beat my current solution?

The scan tells you upfront — a machine-generated verdict, in writing, with data. In production, every solve is checked against your own baseline before billing: if we don't win, you don't pay — and you keep the comparison report. Our incentive is mathematically identical to yours.

How fast is a solve, really?

Sandbox solves are near-instant (simulator-backed). Hardware solves depend on QPU queues: typically minutes to a few hours; the console shows live queue estimates per platform before you commit, and routing always picks the best price/queue trade-off available.

What if my problem isn't in the library?

Launch a Discovery Run from the console: the agent swarm attacks your problem class, priced per compute with an upfront estimate. If it finds a winning recipe, it ships to your account first. Demand writes the roadmap.

How does support work?

Async and fast: in-console assistant with full context of your runs, evidence-linked docs, and engineers behind it for the hard cases. Most issues resolve in minutes because every run is fully inspectable — yours and ours.

How is our data handled?

Our design goal is that your data is formulated into circuit parameters client-side where possible — so raw business data doesn't need to leave your perimeter for most problem classes. Jobs run through major clouds' quantum services, and every run will be auditable via its evidence URL. SOC 2 and a published DPA are on our roadmap before general availability — we'll say when they're done, not before.

Quantum advantage is largely unproven today. Isn't that a problem?

Correct — and it's our business, not our bug. We never claim advantage that isn't there. We measure where it doesn't hold, publish the negative verdicts everyone else buries, and map the crossover point where it will. If quantum arrives late, the referee's archive only grows more valuable. If it arrives on time, we own the map of where it landed first.

Couldn't anyone build this? Why you?

Technically, yes — the code is glue, the libraries are open. But everyone capable is structurally blocked: academia gets no tenure for maintaining a verification ledger; vendors can't publish negatives on the industry they sell (Google pays XPRIZE precisely so a neutral third party exists); consultancies monetize the ambiguity a public ledger destroys. Our edge is a proven veracity methodology already in production, a near-zero cost structure that outlasts funded startups, and a compounding dataset of verified negatives nobody can buy.

Where does this go — what's the endgame?

The ARM model for the quantum era: invisible, small by design, a royalty on every useful computation — on every machine, forever. We start as ~90% authority (verdicts, evidence, subscription) and grow the licensing arm as recipes cross the advantage line. Founded a decade early, on purpose — because the archive compounds while we wait.

"Every solve will make the library smarter. Every Discovery Run will add a recipe the whole industry can one day license. You're early to a compounding asset."
Get early access →
Why we exist, and why we're starting a decade early → manifesto coming soon