A living simulation of the real world, populated by digital twins of real people. Your twin experiences the world for you — and tells you what it found.
Five stars from someone whose taste, budget, and tolerance for noise have nothing to do with yours.
You mention a pencil once and drown in pencil commercials. Targeting knows your tags, not your taste.
Will you like the job, the city, the person? Today the only way to find out is to spend the year finding out.
The missing piece isn’t more data about everyone else.
It’s a working model of you.
Build a twin from fun quizzes, your interests, and — as trust grows — your inbox and socials. Then send it out. Tonight, 1,000 copies of your twin visit 1,000 restaurants in the simulated city: same taste, different tables, real-world friction (weather, wait times, crowds).
You get back one answer, in your own voice: “Go to the one on 5th. You’ll order the short rib. You had Thai on Tuesday.”
restaurants, activities, products — as you
quests, races, rooms — with other twins & people
what you’d be good at, enjoy, who you’d get along with
One chat-centric surface for mockup, web, desktop, and mobile — screens are data, so the demo is the onboarding. The simulation visual replays real recorded agent runs (zero inference cost per visitor). Each audience gets the demo that sells them.
Built on the open multi-agent simulation architecture from Google Cloud Next ’26 (ADK + Agent-to-Agent protocol, tick engine, cached replay) — adapted from runners on a route to twins in a world.
Twin Conversion Rate — of everything the twin recommends, how much does the real human actually do?
TCR simultaneously proves accuracy to users, prices the ad product, and validates the enterprise simulator. One number, whole company.
From day one, the ether makes verifiable predictions on real-world events — logged to an append-only, timestamped calibration ledger and scored (Brier) when events resolve. Internal only. No betting product, no advice — just an accumulating, auditable accuracy curve.
Hash-chained entries. A track record you could have edited is worth nothing; ours can’t be.
Industry-standard calibration scoring against resolved outcomes.
The artifact every enterprise asks for first: “prove your simulator predicts reality.”
| Stream | Mechanism | Phase |
|---|---|---|
| Consumer tiers | Free twin → paid memory & accuracy tiers | 1–2 |
| Commerce | Twin wishlists → merchant referral fees · “Keep my twin running” round-up | 3 |
| AdTwin | Advertisers pitch the twin — sandbox → consideration → converted | 3–4 |
| Enterprise simulation | Consented cohort twins test products, messages, scenarios | 4–5 |
| Prediction (internal) | Calibration ledger — the sales asset behind enterprise deals | 2+ |
The consumer game is the on-ramp — and the consented-data engine — for the enterprise simulator where the real revenue lives.
Today’s targeting guesses from tags. AdTwin asks the one agent that actually knows the customer: their twin. The twin watches every pitch so the human never has to — and surfaces only what genuinely fits. The twin is the user’s agent. Pay-to-pitch, never pay-to-win.
Test 50 creative variants on headless twin cohorts before spending real media budget. Pennies per pitch.
Pitch real users’ twins. The twin decides fit — a brand-new, dirt-cheap ad unit.
Twin showed its human, human acted. Premium pricing on true conversion — measured by TCR.
Enterprises already pay for synthetic audiences — the category has drawn over $1.5B in venture funding with buyers like CVS Health, BlackRock, and Microsoft. But their personas are demographic guesses. Ours are consented twins of real people, sharpened daily by real behavior.
How will 40,000 twins in your market react to this speech, product, or news cycle — before you ship it?
Not just people — products, venues, systems get twins. Real-world physics via the NVIDIA stack as the ether deepens.
With clinical partners: scenario modeling for population response — outbreaks, interventions, recovery patterns.
Aggregated, anonymized cohort simulations only. Individual twins are never sold. Medical applications pursued as research with appropriate partners and oversight.
World engine on Nemotron 3 Ultra (live today via NIM). Safety via Nemotron Content Safety. Twin distillation (big-model teacher → compact twin models). Omniverse-class physics on the roadmap.
Asks: Inception compute credits · NIM production guidance · technical review of the distillation pipeline.
Ether scaffolding from the Cloud Next ’26 open multi-agent architecture (ADK + A2A). Pure-GCP stack: Cloud Run, Identity Platform, Firestore, Secret Manager, Cloud Build. Gemini Flash powers the public demo.
Asks: Startup/credits program · Maps Platform guidance for live-only usage · early access on agentic commerce (UCP).
Quantinuum is built on NVIDIA and Google Cloud technology. References describe our stack, not a partnership or endorsement.
| Phase | Ships | Gate |
|---|---|---|
| 0 · Promote ← now | This deck · marketing refresh · interactive mockup (replay + audience router) | private links to NVIDIA / Google / investors |
| 1 · Soft public | Live demo chat (Gemini via hardened proxy) · waitlist | rate limits + billing alarms proven |
| 2 · Closed alpha | Accounts · persona carryover · “see yourself simulated” | consent + data-delete working |
| 3 · Product | Desktop app · AdTwin sandbox · calibration ledger running | TCR measurement live |
Already real: Nemotron 3 Ultra inference verified · GCP foundation (owner-controlled, SOC 2-ready posture) · chat-centric product frame · this funnel.
Gio · TensorVerse.ai (NVIDIA Inception member) · tensorverseae@gmail.com · tensorverse.ai/quantinuum