Working template

AI & robotics technical diligence checklist.

The evidence to request from early-stage and scale-up companies, claim by claim.

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Company or project

Prepared by

Date

Claims and evidence

For each claim: the evidence and how far it holds. Distinguish demonstrated, reported and unverified claims.

Claims and evidence: entry 1
Claim
Evidence source and date
Status
Reproducibility
Limitations
Confidence
Unresolved question
Proposed validation

Early stage

Problem, user and why the proposed technology is necessary.
Demo conditions, evaluation dataset, baselines and independent reproduction.
Proprietary contribution versus third-party models, software and hardware.
Data provenance, access rights, quality and dependencies; specialist legal review where needed.
Team capability, ownership of critical knowledge and hiring gaps.
Next technical milestone, experiment, resources and failure condition.
Customer validation and assumptions behind the route to revenue.

Scale-up

Performance across sites, users and edge cases; failures and incident handling.
Integration effort per deployment and customer-specific engineering.
Infrastructure, model, hardware, support and maintenance costs.
Reliability, monitoring, security controls and update or change process.
Manufacturing, supply-chain, service and capacity constraints for robotics.
Deployment backlog, repeatability, engineering organisation and roadmap risks.
Customer concentration and evidence supporting unit-economics assumptions.

Material risks

Management questions

Specialist-review needs

Recommended tests

Decision dependencies

A checklist does not establish a company's investment merit and does not replace a company-specific technical assessment or specialist legal review.

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AI & robotics technical diligence checklist.

Claims and evidence

Claims and evidence: entry 1

Early stage

Scale-up

Material risks

Management questions

Specialist-review needs

Recommended tests

Decision dependencies

Discuss this brief