Quantified Yield & Value for Energy Response Networks
AI that forecasts a data center's electricity load, shaves the demand peaks that set the bill, and dispatches the response — automatically.
Mission
A data center's largest controllable cost isn't the energy it draws — it's the demand peak that sets the bill.
Demand charges are fixed by a single highest interval each month. A few unwatched minutes of coincident load can dictate an entire billing cycle — and most operators never see the peak coming.
QYVERN forecasts that peak before it forms and dispatches the response to flatten it, turning volatile, unpredictable load into a lower, controllable curve — with the same workloads served.
Pipeline
Every site runs the same autonomous cycle — sensing conditions, forecasting the peak, optimizing the response, dispatching it, and learning from the result.
Ingest meter, weather, market-price, and workload telemetry in real time — validated and gap-filled.
Probabilistic day-ahead and intraday load forecasts with quantile bounds on the likely peak.
Solve for the lowest-cost load-shift schedule that clips the peak within every operational limit.
Issue setpoints to batteries, thermal, and deferrable compute — and verify realization against plan.
Score every dispatch against outcome and retrain on the residual. The loop compounds each cycle.
Platform
Forecasting, optimization, and dispatch in one system — designed to run unattended and prove out every decision it makes.
Day-ahead and intraday load forecasts with quantile bounds, so the plan targets the peak you're most likely to hit — not just the average.
Setpoints to batteries, thermal storage, and deferrable compute at sub-minute latency — with realization verified interval by interval.
Cost-aware peak shaving that respects every SLA, ramp limit, and storage constraint — optimizing the bill, not just the load line.
Every dispatch is scored against its outcome and the model retrains on the residual — accuracy compounds the longer it runs.
Metrics
Illustrative figures — placeholder metrics representing typical outcomes across managed sites.
Illustrative. Unmanaged demand vs. the QYVERN-managed curve held under the peak cap.
Roadmap
Per-site savings are the wedge. The same forecasting and dispatch core scales outward — into a fleet, and then into the wholesale market.
Forecasting and demand-charge reduction, live per site today and learning from every dispatch.
Pool flexible load across sites into one coordinated, dispatchable resource — shaving peaks in concert.
Bid aggregated capacity into wholesale energy and ancillary-service markets — a virtual power plant that earns.
Request Access
Send twelve months of interval data and we'll return a modeled peak-shaving profile and a demand-charge estimate — no hardware, no commitment.
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