Most facilities discover energy waste 30-60 days after it happened when the utility bill arrives. Signal Energy Analytics catches it in real time and tells you exactly which system, schedule, or setpoint is responsible.
Four core analytics, all weather-normalized and tied to building schedule.
Electric, gas, water, steam, chilled water, hot water every meter normalized and trended. 15-minute resolution. Multi-year history.
Off-hours consumption, weekend baseline drift, schedule mismatches. Tied to your building schedule, not a generic 9-5.
Compare apples to apples. CDD/HDD-normalized models so cold-snap consumption does not look like waste.
Building-to-building comparisons within your portfolio. Identify the underperformers fast.
A common pattern: AHU schedules are correct in the BAS but the actual operation extends 90 minutes past close. Signal flags the discrepancy weekly, ties it to specific equipment, and quantifies the kWh and dollars wasted.
Most teams recover 5-15% of consumption in the first six months by addressing the schedule and setpoint issues Signal surfaces.
How this looks in your stack.
model: "hdd_cdd_regression" window: "24mo" drivers: - "hdd_65" - "cdd_65" - "occupancy_pct" flag_when: residual_pct: "> 10" duration_hr: "> 4"
On-premise by default. Cloud-deployable when required. Your facility data never leaves your network.
TLS everywhere, secrets in vault, row-level security on every query. Containerized and isolated so one service going down never takes the rest with it.
A·IQ is built by Arcis FM, a Service-Disabled Veteran-Owned Small Business (SDVOSB). Set-aside eligible for federal contracts. CAGE 14DG6 · UEI Z95MQL2KEYG3.
Engineer and operator questions on this capability.
Electric, natural gas, water, steam, chilled water, hot water plus production utilities like compressed air and process water on industrial sites.
Direct meter polling via BACnet/Modbus, Green Button (ESPI) for utility-side data, manual CSV upload, and REST API for third-party meters.
For most teams, yes. Signal covers consumption analytics, anomaly detection, and benchmarking the work usually spread across utility portals, spreadsheets, and EMS dashboards.
CDD/HDD regression for HVAC-driven loads, occupancy and production drivers for non-HVAC. Models update continuously.
Energy analytics is consumption. Power metering is demand. Green Button is the bill.
Send us 12 months of utility data. We will benchmark your portfolio, identify the bottom-quartile buildings, and quantify the recoverable consumption.
