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AI now shapes investigations and high-stakes decisions. AVAAS certifies the system where its output drives action.

DOJ and FBI investigative analysis, DoD decision support, and FEMA disaster response use AI to prioritize, recommend, and flag. When the output is wrong, an investigation targets the wrong person or aid reaches the wrong place. AVAAS certifies the system at the point its output drives a decision.

OMB M-25-21OMB M-25-22FRE 707ReliabilityHuman oversight
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Where AI acts on a person

The decision point in justice and defense

Here the AI acts when it generates an investigative lead, scores a case or a target, or recommends a response. An output built on a flawed model sends people and resources the wrong way.

When AI output becomes evidence, it has to be as reliable as an expert would be. That is the standard proposed Federal Rule of Evidence 707 is reaching for.

What keeps you exposed

What keeps agencies exposed

Federal high-impact duties

Testing on a deadline

OMB M-25-21 and M-25-22 require pre-deployment and pre-award testing, monitoring, and documentation for high-impact AI. Agencies must document implementation or discontinue the system.

Courtroom reliability

Output that has to survive in court

Proposed Federal Rule of Evidence 707 would hold machine-generated evidence to the same reliability standard as an expert, with a realistic effective date of December 2027. Louisiana already passed an AI-evidence law in 2025.

Leads from a model

A lead is only as good as the system

An investigative lead or a target score built on a flawed model sends agents and resources the wrong way, and the error can reach a person before anyone catches it.

This is already happening
Dec 2027
Proposed Federal Rule of Evidence 707 would hold machine-generated evidence to the same reliability standard as an expert witness, with a realistic effective date of December 2027.
U.S. Judicial Conference Advisory Committee, 2025
How AVAAS adds value

Evidence the output is reliable enough to rely on

Will the output hold up to reliability scrutiny?

AVAAS produces documented, third-party evidence of how the system performs, the validation reliability standards are reaching for.

Is human judgment actually in control?

AVAAS evaluates whether human oversight is meaningful at the point the output drives a decision.

Does the system fail unevenly?

Five structurally independent validators test for demographic disparity and failure patterns using causal attribution.

You get documented, third-party evidence that an analysis or decision-support system is reliable enough to act on and to defend if it is challenged.

Related AVAAS coverage: Certification · Evidence Ledger · Regulation Checker. Or run the free AI Exposure Assessment.

See where your decision-support AI creates liability.

Tell us where AI informs an investigation, a target score, or a response decision, and we will scope an AVAAS certification to the exposure.

Ready to start now? Certify Your AI →  or  email [email protected]