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AI agent for energy engineers

Energy Audit Savings Verification Agent

Verified savings for each efficiency measure

AnalysisMonitoringReportingScience and research
See how it worksGet access
Energy Audit Savings Verification Agent: what goes in, what the agent does and what you get

What it does

After efficiency measures are installed, clients want proof that the savings are real. Each month this agent pulls meter and weather data and runs a baseline model adjusted for weather and occupancy, using a measurement and verification plan for each measure. It compares actual savings with the audit's estimates. When savings fall short by more than the threshold, it looks for causes, such as controls overridden by staff or changed schedules, and checks again once the cause is fixed or explained. It drafts a savings report. The engineer approves the report before it goes to the client. Edge case: a site that added a new building wing during the period gets the baseline adjusted for the added area, with a clear note so the client understands the change.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Monthly savings check 2 USES A TOOL Pull meter and weather data 3 USES A TOOL Run baseline model with adjustments 4 DOES Compare actual savings with estimates 5 CHECKS THE RESULT Are savings within the threshold of estimate? If not: look for control overrides or schedule changesand adjust. Back to step 3. 6 DOES Draft savings report 7 YOU APPROVE Engineer approves report 8 RESULT Report sent to client
Read the steps as a list
  1. Monthly savings check
  2. Pull meter and weather data
  3. Run baseline model with adjustments
  4. Compare actual savings with estimates
  5. Are savings within the threshold of estimate?If not: look for control overrides or schedule changes and adjust. Back to step 3.
  6. Draft savings report
  7. Engineer approves reportThe agent waits here for your OK.
  8. Report sent to client

How it decides

It compares weather-adjusted actual use with the baseline and flags measures with savings below the threshold percentage of estimate.

  • Adjust for weather with degree-days
  • Flag measures under the threshold
  • Note changes in building use

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Savings threshold (default 80% of estimate)
  • Baseline model type
  • Reporting interval
  • Report format

What keeps you in control

It always asks you first

  • Sending reports to clients

Hard limits

  • Never changes building controls

It stops when

  • Done: report sent
  • Stop: meter data missing

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensFor the April review at Lakeside Middle School, the agent pulled meter and weather data and adjusted for 410 heating degree-days. The LED retrofit saved 11,800 kWh against an estimate of 12,000. The boiler controls measure saved only 58% of its estimate, below the 80% threshold. The agent went back to the trend logs, found a schedule override set to 24/7 since March 2, and reran the model. The engineer approved the report with that note.

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