Evidence assurance capability

AI-ASSISTED DECISION EVIDENCE VALIDATION

AI can produce impressive research. The question is whether the evidence beneath it can support the decision.

What we may examine

Whether cited sources exist and are correctly represented
Whether a source supports the proposition attributed to it
Entity, period and jurisdiction matching
Circular sourcing and source lineage
Omitted primary records
Unsupported inferential steps
Contradictions between generated analysis and underlying records
Where authoritative or private evidence is still required

What this is not

This is not an AI-detection service. Aperture does not attempt to determine whether ordinary text “sounds AI-generated”.

The relevant question is whether the material factual proposition is adequately supported for the intended reliance.

AI output is not evidence. AI capability is not authority.

Discuss an AI-Assisted Evidence Question See Fees

Illustrative situation

An AI-written report has convincing references

A team receives a polished report with references. Before using it, you need to know whether the citations exist and support the conclusions.

Do the original sources actually say what the report attributes to them?

What we would examine: Check each material reference, passage, date and quotation. Trace circular citations and separate factual support from inference.
What you could receive: A claim-by-claim citation review with support status, corrections and unresolved items.

How a finding could read, if the evidence supported it

The cited document exists, but the reviewed passage does not support the conclusion attributed to it. That claim requires another source or correction.

Why this helps: Your reviewer can repair the evidence record before the report influences a decision or publication.

This is an illustration, not a completed client assignment or a finding about a real organisation. The actual evidence determines the result.