Diagnose and decide

Turn scattered energy data into a prioritized action plan.

The EnergyAI Diagnostic Sprint reviews the evidence already available, identifies the most important performance and data gaps, and defines the next analyses that are worth pursuing.

When this service is useful

Use the review when the decision needs clearer evidence.

Energy information is spread across bills, meters, spreadsheets, building systems and operating records.
Leadership needs a clear priority list before commissioning a wider audit, software platform or investment study.
Existing dashboards or reports show data but do not support a confident decision.
The organization wants to test whether forecasting, anomaly detection, benchmarking or optimization is practical with the available data.
A site or portfolio needs an independent opportunity screen before procurement or capital planning.

What NEI reviews

Evidence, assumptions and decision context.

Utility bills, tariff context and available interval data.
Major loads, operating schedules and facility context.
Existing dashboards, audits, studies or proposals.
Data completeness, consistency, frequency and accessibility.
Baseline assumptions, performance indicators and candidate analytics use cases.

Information requested

Start with the minimum useful evidence.

Data limitations are recorded explicitly and used to shape proportionate next steps.

Up to 12 months of recent utility bills where available.
Interval electricity or other energy data where available.
Site, building or process summary and major equipment list.
Existing reports, proposals, dashboards or targets.
Known pain points, constraints and intended decisions.

Client deliverables

Clear outputs for the next decision.

Data-readiness assessment

A structured view of available data, key limitations and what can be analyzed credibly.

Energy opportunity screen

Prioritized operational, analytical, measurement and potential investment opportunities.

Evidence-gap register

Missing information, measurements or validation steps that materially affect the decision.

Executive action brief

A concise summary of findings, priorities, risks and recommended next actions.

Review meeting

A discussion of the findings, assumptions and practical route forward.

Data readiness and responsible AI

Connect every data point and model to a decision.

The sprint distinguishes ordinary reporting, diagnostic analytics and justified AI use cases so complexity is added only when it improves the workflow.

Decision questions answered

Which energy or operating questions are ready for analysis now?
Which apparent opportunities are supported by data, and which require measurement?
Where could analytics or AI add value beyond ordinary reporting?
What should the organization prioritize during the next 30–90 days?

Data-readiness ladder

Accessible: relevant data can be obtained reliably and lawfully.
Contextualized: units, timestamps, asset boundaries, tariffs and events are understood.
Quality-checked: gaps, duplicates, drift, resets and abnormal periods are identified.
Decision-linked: every metric or model connects to an action, owner and success measure.

Read the AI-readiness guide →

Evidence base

The sprint is informed by energy-management principles such as measurement, objectives and continual review in ISO 50001, implementation lessons in the IEA Energy and AI report, and the lifecycle risk structure of the NIST AI Risk Management Framework. Referencing these sources does not imply certification or endorsement.

Engagement sequence

Five focused steps.

Define the decision and site context.
Confirm the minimum useful data request.
Review, clean and interpret the supplied evidence.
Screen credible opportunities and analytics use cases.
Deliver the report and executive discussion.

Scope boundary

Unless separately scoped, the sprint is not an investment-grade energy audit, guaranteed-savings assessment, detailed engineering design, software implementation, continuous monitoring or installation service.

Identify the highest-value next analysis before expanding the project.

Start with the decision, available evidence and the outcome the organization needs.

Request a diagnostic discussion

Engagement at a glance

A defined decision engagement.

Scope

2-3 weeks · AED 18,000-35,000

Typical inputs

Utility bills and tariff information
Interval data where available
Operating schedules and asset context
Known data gaps and management questions

Decision-ready output

A data-readiness score, opportunity map, quantified ranges, evidence gaps and a prioritized action sequence for management.

Not included

Metering or sensor installation
Detailed engineering design
Software implementation
Guaranteed savings or investment returns

Final scope and fee are confirmed after a 20-minute fit call and review of available information.

Request a fit call See sample outputs

Fit and frequently asked questions

Use this offer when the next decision matters more than another generic report.

When is this the right first step?

When energy data exists but decision-makers need a fast, independent view of what is usable, material and worth testing next.

Do we need perfect interval data?

No. Data gaps are assessed explicitly and become part of the recommendation.

Will NEI build a dashboard?

Not in the diagnostic. A digital tool is considered only after the workflow and decision value are proven.

Can vendors participate?

Yes, but evidence and claims are reviewed independently and conflicts are disclosed.

Australian application

Turn interval, tariff and operating data into a decision.

For Australian campuses, councils, commercial portfolios and industrial sites, the sprint can examine load shape, demand exposure, rooftop solar interaction, operational constraints and data readiness—then identify the next evidence-backed test rather than prescribing a platform.