Free Due Diligence Checklist

Energy-AI Due Diligence Checklist

Energy-AI Due Diligence Checklist Cover

18 decisive questions to validate "black box" energy startups. Separate AI wrappers from grid-grade innovators and de-risk investments fast.

18
Questions
5
Sections
2026
Updated
18
Questions
5
Sections
2026
Updated
Key Outcomes

What You'll Validate

Critical checks to separate hype from grid-grade technology

Real AI Test

Expose "AI wrappers" and verify defensible IP

Data Moat

Assess proprietary data, quality, and rights

Market & Physics Fit

Validate grid constraints, regulation, and resilience

Overview

Executive Summary

This checklist equips Investment Directors and CIOs to interrogate Energy-AI startups with precision. It prioritizes physics-grade reliability, defensible data moats, and regulatory alignment so you can de-risk capital allocation.

Use these questions in early meetings to separate marketing claims from grid-grade innovation. The checklist highlights failure modes, data rights, scalability limits, and governance risks before deeper technical audits.

Code Must Respect Voltage

"Move fast and break things" doesn’t work for energy. This checklist helps you uncover risk before it becomes operational failure.

Checklist Preview Energy AI Market Context
Checklist Sections

Validation Framework

01

Real AI Test

Confirm model architecture, retraining cadence, and failure handling.

02

Data Moat

Verify proprietary datasets, data rights, and quality resilience.

03

Market & Physics Fit

Assess grid constraints, compliance, and extreme-event testing.

04

Scalability & Governance

Evaluate unit economics, onboarding friction, and security posture.

Full checklist available in the downloadable guide

Energy-AI Due Diligence Checklist

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Complete Checklist

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5 checklist sections
Red-flag detection
Grid-grade risk filters

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