The real-time grid intelligence engine
Voltpathio's platform ingests ISO grid stress signals, BMS telemetry, and weather data to generate load-shaping recommendations at 200ms decision cycles.
Data ingestion → prediction → dispatch
94% peak demand forecast accuracy at 15-minute horizon
The demand forecast engine is a gradient-boosted ensemble trained on 18 months of ISO grid event data across PJM and MISO, cross-referenced with building thermal mass coefficients, occupancy schedules, and National Weather Service mesoscale analysis data. It outputs a probabilistic peak demand estimate with confidence intervals every 60 seconds.
Accuracy degrades to 85% at 45-minute horizon — still sufficient to issue HVAC pre-conditioning commands before the demand window opens. We do not claim accuracy we haven't measured: the 30-day pilot generates site-specific backtesting against your actual billing intervals so you can verify the numbers before committing to a full subscription.
Built for operational infrastructure
AES-256 data encryption at rest. TLS 1.3 for all API and BMS adapter traffic. Designed with SOC 2 Type II controls — audit report available to Enterprise customers on request.
Per-building permission scopes with read-only, operator, and admin roles. Immutable audit log for every load command issued — timestamp, building ID, zone, kW delta, and operator identity recorded. Operators can override any automated command in real time.
Multi-region cloud architecture with active-active redundancy on the dispatch layer. No single point of command failure. If the cloud layer drops, BMS adapters fall back to pre-configured local guardrail rules — demand protection continues even during connectivity loss.
Ready to connect your first building?
BMS connection in under 48 hours. See your demand charge exposure in the first session.