AI SECURITY · ASSURANCE · STANDARDS

Operational assurance infrastructure for AI security.

ODA3 Institute connects AI governance requirements to operational AI security controls, evidence, provenance, verification and bounded assurance through the GAISSF Ecosystem, applied research and practitioner guidance.

Where AI Governance meets Operational Reality.

03 AUGUST PAI-SF™ Framework Physical AI Security Framework Published. Preview →
VERIFIABLE OUTPUT

Published work, not implied traction.

Counts reflect the current public website release and describe different publication families rather than a combined adoption metric.

START WITH YOUR DECISION CONTEXT

Built for practitioners. Structured for decision-makers.

ONE CONNECTED ASSURANCE ARCHITECTURE

Govern. Classify. Respond.

Four published frameworks connect organizational requirements with incident records, response procedures, physical-system safeguards and evidence.

Explore PAI-SF™ → Explore the GAISSF Ecosystem →
LATEST INSIGHTS

Current practitioner guidance.

Recent publications demonstrate active work without presenting publication volume as enterprise adoption.

Editorial illustration representing operational AI assurance, structured participation, evidence, and independent governance
Institute Announcement · ODA3-2026-08-INS-087 · August 7, 2026

ODA3 Institute Launches Membership Programme for Operational AI Assurance

A structured participation pathway for practitioners, researchers, academics, organizations and standards participants, built around contribution, independence and explicit boundaries.

Read the publication →
Editorial illustration for EU AI Act Article 50 transparency and operational evidence
Regulatory Intelligence · ODA3-2026-08-INS-086 · August 5, 2026

Introducing the ODA3 EU AI Act Article 50 Transparency Toolkit

A free, evidence-first toolkit for screening applicability, recording evidence and supporting implementation of EU AI Act Article 50 transparency obligations.

Read the publication →
Abstract editorial illustration showing AI risk mapping connected to layered operational assurance and evidence controls
Standards Development · ODA3-2026-08-INS-085 · August 5, 2026

Where Risk Mapping Ends and Assurance Begins

How Google's SAIF and ODA3's GAISSF™ Ecosystem can work together through a practitioner method for accountability, evidence, incident response and physical-effect assurance.

Read the publication →
Editorial illustration of network-connected humanoid and quadruped robots examined through hardware and supply-chain assurance controls
Regulatory Intelligence · ODA3-2026-08-INS-084 · August 5, 2026

The FCC Just Made Robot Hardware a National-Security Question — Here's the Assurance Gap Behind It

A source-bounded analysis of the FCC Covered List action on advanced robotic devices and the operational hardware-assurance gap behind it.

Read the publication →
Editorial illustration of an autonomous drone navigating an ambiguous indoor environment under independent assurance controls
Applied Research · ODA3-2026-08-INS-083 · August 4, 2026

When AI Controls a Drone: What Physical AI Security Requires Beyond Model Safety

Drone-Bench shows why strong component performance does not by itself establish safe end-to-end physical autonomy.

Read the publication →
Editorial illustration for EU AI Act Article 50 transparency and operational evidence
Regulatory Intelligence · ODA3-2026-08-INS-082 · August 4, 2026

EU AI Act Article 50 Takes Effect: The Operational Evidence Gap Behind AI Transparency

What enforceable EU AI Act Article 50 transparency duties mean operationally—and why evidence that disclosure and marking controls work now matters.

Read the publication →
Browse all 89 publications →
OPERATIONAL TOOLKITS

EU AI Act Article 50 Transparency Toolkit

Version 1.0 · Published 5 August 2026

Screen potential Article 50 applicability, capture supporting evidence, and apply obligation-specific implementation guidance.

Explore the Toolkit
CURRENT OPERATIONAL STATUS

Published, developing and not operational—stated separately.

PUBLISHED

GAISSF™ v1.0

Governance and assurance framework.

PUBLISHED

UAIF™ v1.0

AI incident classification and taxonomy.

PUBLISHED

AI-IRF™ v1.0

AI incident-response framework.

PUBLISHED

PAI-SF™ v1.0

Physical AI security framework.

AVAILABLE

Machine-readable schemas

Published schema and reference resources.

DEVELOPING

Assessment methodology

Methods and evidence pathways under development.

DEVELOPING

Training pathways

Nine-domain curriculum in development.

DEVELOPING

Organizational certification

Organizational certification remains under development; no accredited certification-body service is represented as operational.

UPDATED

August 3, 2026

Website publication status snapshot.

THREE WAYS TO START

Choose the level of detail you need.

01 · RESEARCH

Read the published research

Start with formal reports, evidence-bounded incident analysis and practitioner publications.

Browse Research Publications →
02 · FRAMEWORKS

Access the framework suite

Review the governance, classification and response layers, their documentation and schemas.

Start with the Frameworks →
03 · ENGAGEMENT

Discuss an enterprise requirement

Describe the implementation, evidence, research or collaboration context you need to evaluate.

Start an Enterprise Enquiry →
INTENDED ENTERPRISE OUTCOMES

What the architecture is designed to support.

These are intended implementation outcomes, not promises of guaranteed security, compliance or financial return.

Clearer control ownership

Defined accountability and applicability across AI-system lifecycles.

Consistent incident classification

Shared records for severity, causality, impact and confidence.

Coordinated response decisions

Aligned security, governance, legal and operational actions.

Traceable evidence

Documented support for findings, limitations and evaluation.

Assessment preparation

Structured criteria and evidence paths for future evaluation.

Evidence Readiness Pilot →

Explicit limitations

Unsupported conclusions and materially absent evidence are recorded.

THE ODA3 EVIDENCE STANDARD

We state what the evidence supports—and what it does not.

ODA3 publications identify source basis, material limitations and notably absent evidence. We do not inflate threats or present unsupported conclusions as established fact.

Review the evidence methodology →
ODA3 INSTITUTE

An AI security standards, applied-research and operational-assurance organization.

ODA3 Institute publishes the GAISSF Ecosystem and develops assessment, practitioner-capability and certification infrastructure that connects AI governance requirements with operational implementation and evidence. ODA3 Institute is not currently an accredited certification body.

No vendor sponsorship determines research findings.
Framework mapping does not establish regulatory approval or legal compliance.
Planned assessment, training and certification capabilities are not represented as operational.
About ODA3 Institute →
PUBLISHED RESOURCES

Human-readable guidance and machine-readable implementation resources.

INSTITUTE PATHWAYS

Research, capability development and engagement.

STANDARDS & REGULATORY MAPPINGS

Documented relationships, not implied affiliation.

Published ODA3 crosswalks document relationships with selected standards and regulatory requirements, including NIST AI RMF, ISO/IEC 42001 and the EU AI Act.

Relationship boundary

A crosswalk documents correspondence. It does not establish endorsement, equivalence, regulatory approval or legal compliance.

Browse all published crosswalk packages →
ENTERPRISE & INSTITUTIONAL ENGAGEMENT

Start with the requirement, evidence and operating context.

ODA3 evaluates enquiries against documented scope, current capability status, confidentiality, data-handling, independence and publication requirements.

Discuss an Enterprise Engagement →