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ENERGY AND OPERATIONAL INTELLIGENCE

Find where your facility can operate more efficiently.

Turn meter readings into evidence-backed operational findings, estimated improvements and clear next steps.

Create an AccountCustomer Login

After registration, you can request access to the demonstration project.

From raw readings to practical action.

  1. 1

    Observe

    See how energy, demand and major operating areas behave.

  2. 2

    Understand

    Identify what changed and which loads contributed.

  3. 3

    Improve

    Find operating patterns and practical opportunities.

  4. 4

    Verify

    Compare performance after the change.

Outcome A

See when energy use does not match normal operations.

Finding: A major load started earlier than the normal operating window.

Investigation cue: Confirm whether the earlier startup is operationally required.

Illustrative product example using simulated data.

Morning load profile

Compared with the previous four-week average

Illustrative
Operating hoursUnusual early window5 am7:309 am12 pm
Today4-week average
+18% before hours
Chiller Plant led the early rise

Outcome B

See what caused the peak—not only how high it was.

Finding: Two major loads overlapped during the highest demand interval.

Investigation cue: Review whether startup sequencing can be adjusted.

Illustrative product example using simulated data.

Maximum demand breakdown

8:00 am Tuesday · 842 kW peak

Illustrative
Peak 842 kW · 8 am6 am8 am10 am12 pm
  • Chiller Plant37%
  • Production Line 232%
  • Production Line 117%

Outcome C

Compare performance after an operating change.

Finding: Before-hours energy decreased after the schedule adjustment.

Illustrative product example using simulated data.

Before / after comparison

Matched operating window after schedule adjustment

Illustrative
5 am7:309 am10 am
Before changeAfter change
Before 370 kW
After 303 kW
Change -18%

How AI Works

See how AI turns your question into a grounded answer.

AI understands the question and coordinates the analysis. The underlying findings come from authorised data and defined calculations—not unsupported guesses.

  1. 01

    You ask a question

  2. 02

    AI understands intent

  3. 03

    System retrieves data and calculates

  4. 04

    AI explains the findings

  5. 05

    You verify the result

Example question

Scripted
Ask

Where should the operations team investigate first?

Selected evidence

Period

Last 7 days

Comparison

Previous 4 weeks

Area

Chiller Plant

98%

Evidence completeness

Calculations run only on authorised meter scope

Observed

Before-hours energy use increased.

Analysis

The Chiller Plant contributed the largest share and was active during the weekly demand peak.

  • Chiller Plant37%
  • Production Line 232%
  • Other loads31%

Investigate next

Confirm the required cooling lead time and review the startup sequence.

Verification

Compare before-hours energy and morning demand over the following two weeks.

Measured facts, calculated findings and estimated scenarios are clearly distinguished. Public example is scripted and synthetic. No production AI endpoint is called.

Measured

Directly from authorised meter data.

Calculated

Produced using defined analytical methods.

Estimated

Scenario-based and clearly labelled.

Measured facts, calculated findings and estimated scenarios are clearly distinguished.

Get started

Explore the Energy Portal with a registered account.

Create an account, then request access to the demonstration project to experience the customer dashboard using simulated facility data.

Create an AccountCustomer Login

Access to the demonstration project is assigned by Bao Service.

Path to the demonstration project

  1. 1Create account
  2. 2Request access
  3. 3Explore cust-demo