T3QML/PDEEnergy & Utilities
Renewable output forecasting
Wind/solar forecasting via QML — advantage unproven; classical ML competitive.
Sector
Renewables
Likely buyer
Utilities; traders
Hardware gate
Research
Taxonomy
fragility-reliability × accelerating
No live demo yet — QML forecasting advantage unproven vs classical ML. The paradigm-honest position: this use case is demonstrated with crossover analysis, not theater.
GTM talk track
Track, don't lead.
OGSM — product operating frame
Objective
Watching brief.
Goals
- Track QML
Strategies
- Monitor
Measures
- N/A
OBR — outcome-based roadmap
| Horizon | Outcome we create | Buyer behavior change | Result we measure |
|---|---|---|---|
| Now | Educate | Prospect runs the emulated demo on their own instance data | Booked QPU-time evaluation or paid pilot |
| Next | Revisit | Prospect co-designs a scoped benchmark against their incumbent solver | Documented crossover curve; expansion to production instances |
| Later | Reassess | Prospect standardizes on the workflow or buys an on-prem system | Recurring QPU consumption / system sale; reference case |
Fit notes (honesty gate)
QML advantage unproven.
Ready to run this on real hardware?
Emulation-verified today — the same program runs on a Pasqal QPU unchanged.