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ai energy management for commercial buildings

Cut energy waste in commercial buildings with AI agents you own.

Gaper builds AI agents into your building automation system, meters and CMMS: automated fault detection and diagnostics, envelope inspection reports and retrofit planning. They find the waste, open the fix and prove the savings, and your team owns the code.

30 min building teardown1 savings caseNo platform lock-in
Production
Not another dashboard
Your BAS
BACnet · Niagara · any BMS
In your cloud
Your auth, your data
You own it
Code and runbook handed over
energy waste in commercial buildings

Why do commercial buildings waste so much energy?

HVAC faults, schedules nobody updates and leaks in the building envelope. The data to catch them already sits in BMS trend logs, interval meters and inspection imagery. Nobody has the hours to read it.

01 · Annual energy spend
$141B

spent by U.S. commercial buildings in one year, about $1.46 per sq ft.

Electricity 84%Other fuels 16%
Source: U.S. EIA, CBECS 2018
02 · Wasted on average
~30%

of every kWh a commercial building buys.

WastedUsed
Source: U.S. EPA ENERGY STAR
03 · What better controls do
−57%

average HVAC energy cut with advanced controls on rooftop units.

Standard operation100
Advanced controls43
Source: PNNL / U.S. DOE field trial, 66 units, 8 buildings
Works with the systems already in your buildings:
BACnetNiagara / TridiumENERGY STAR Portfolio ManagerGreen ButtonUtility interval dataIBM MaximoServiceNowDrone / thermal imageryOpenAI · Claude · Gemini
building analytics that act

Building analytics that open the fix, not just the alarm.

Most building analytics software stops at a dashboard. Gaper agents read demand curves, setpoints, thermal passes and utility bills, decide what matters, act in your tools and leave a trace your team can inspect.

Energy demand
1MW25012am6am12pm6pm
Suggested setpoints[$124]/day
80°F70°F12am12pm
── current- - agent-suggested
Facade scanSUMMER '26
[13]critical
[37]low priority
Retrofit forecast
Cost savings
[$0.21M]
Energy savings
[1.2M kWh]
Incentives
[$0.6M]
Payback
[7.2 yrs]
SAMPLE AGENT OUTPUTS · BRACKETED VALUES ARE PLACEHOLDERS
ai agents for facilities management

Three AI agents for the three places commercial buildings leak energy.

01 · OPERATIONS

HVAC Fault Detection & Diagnostics Agent

Automated FDD for the waste your BAS is already logging.

Continuous, monitoring-based commissioning on every AHU, RTU, VAV and meter. The agent catches simultaneous heating and cooling, schedule drift, stuck economizers and sensor drift, then opens the work order in Maximo or ServiceNow with the evidence attached. Predictive maintenance for HVAC, without another dashboard.

In: BMS trend logs, metersOut: work orders, setpoint changes
7%Median annual savings reported from FDD systems, about $0.19 per sq ft. Source: LBNL, 2019
See it on your trend data->
Peak demand · by hourSAMPLE
Insight: Saturday 10pm load matches a weekday. Override left on.
Fault queue
AHU-3 heat + coolWO OPENED
RTU-7 economizerWO OPENED
VAV-412 sensor driftREVIEW
02 · INSPECTIONS

Building Envelope Inspection Agent

Turn drone and infrared thermography into a repair list by morning.

Your inspector or drone partner captures the thermal imaging. The agent detects air leakage, missing insulation, thermal bridges and moisture, pins each defect to a floor and bay, and drafts the building envelope inspection report your team would otherwise spend a week writing.

In: thermal + visual imageryOut: prioritized defect report
Send us a sample inspection->
Anomaly · floors 14 to 18SAMPLE
CRITICALHeat loss around window head. Probable failed gasket. Air leakage.
Draft report · north facade
Critical[13]
Low priority[37]
REPORT 72% DRAFTED
03 · RETROFITS

Energy Retrofit Planning Agent

Know which energy efficiency measure pays back first.

An AI energy audit you can rerun every quarter. It combines utility bills, interval data, equipment age and building energy modeling into a ranked retrofit plan with payback and carbon impact. It drafts 179D and utility rebate paperwork and maps a path to building performance standards like Local Law 97.

In: bills, interval data, asset listOut: ranked plan + incentive forms
Get a sample business case->
Consumption after change[23%] savings
JanJulDec
- - today── after retrofit
Heating load
BeforeAfter
[18%] reduction
Ranked by payback
Retro-commissioning[0.8] yr
LED + occupancy[2.1] yr
VFDs on AHU fans[3.4] yr
Envelope sealing[5.0] yr
why gaper

Most buildings get another analytics platform. You need AI agents that act.

TYPICAL BUILDING ANALYTICS PLATFORM
  • Another dashboard and login for your team
  • Building data copied into their cloud
  • Per-building license with no end date
  • Insights still wait for someone to act on them
GAPER
  • Actions land in Maximo, ServiceNow or your BAS
  • Runs in your cloud, with your auth
  • You own the code; we can run the SLA
  • Evals and guardrails on your real buildings
how we work

From a free AI energy assessment to an agent you own.

Start with one building and one workflow. Verify it against real trend data, then roll it out across the portfolio with a named owner.

01 · 30 MIN
Assess one building

Bring a building and its systems. We size the savings and make the build-vs-buy call before anyone writes code.

Free AI assessment
02 · BUILD
First build

A working agent on your real BAS and meter data, inside your cloud, within a day of access.

Connected agent
03 · 12 EVALS
Prove the savings

Measurement and verification against a weather-normalized baseline, gated by release evals before it touches a live control point.

Savings case + evals
04 · YOURS
Launch with ownership

Code, runbook and monitoring handed over, or Gaper operates it under an SLA. Then roll it out across the portfolio.

Code + runbook
free assessment

Book a free AI energy assessment.

30 minutes with an AI architect. Bring one building and one workflow. You leave with a savings estimate and a build plan, whether or not you work with us.

Your data stays putSingle sites or portfoliosOwners, operators, consultants
faq

Questions facilities teams ask about AI energy management

How can AI reduce energy consumption in commercial buildings?

Most waste comes from HVAC faults, poor schedules and envelope leaks that nobody has time to find. AI agents read BMS trend data, meter intervals and inspection imagery continuously, flag what is wasting energy, and open the fix in the tools your team already uses.

What is fault detection and diagnostics (FDD) for HVAC?

Automated fault detection and diagnostics continuously checks building automation data for problems such as simultaneous heating and cooling, stuck dampers or drifting sensors, and explains the likely cause. Gaper's agent goes a step further: it writes the work order and tracks the fix.

How is this different from building analytics software?

A building analytics platform gives you its dashboard and its roadmap. We build AI agents around your workflow, inside your BMS and CMMS, and you own the code. No per-building license that never ends.

Which building automation systems do you integrate with?

BACnet and Niagara-based BAS and BMS, utility and interval data (Green Button, utility APIs, ENERGY STAR Portfolio Manager), and work order management in Maximo and ServiceNow. If it has an API or an export, we can usually work with it.

Does our building data leave our network?

No. Agents run in your cloud or on-prem environment with your authentication. Gaper never needs a copy of your BAS data on our servers.

How long until we see results?

Timelines depend on the integrations and approvals the workflow needs, so they are scoped up front. Savings are measured against a baseline before launch.

PRODUCTION AI AGENTS FOR BUILDINGS, SHIPPED WITH AN OWNER

Ready to put AI energy management into production?

Book a free 30-minute assessment. We'll find the highest-leverage building workflow and scope the smallest thing worth shipping.

Build, deploy, runYour cloudYou own the code

Stats: U.S. EIA Commercial Buildings Energy Consumption Survey (2018); U.S. EPA ENERGY STAR; PNNL advanced rooftop-unit controls field study (2014); LBNL building analytics and monitoring-based commissioning study (2019). Agent screens show sample output.