Check, disclose, map, and assess
Use the public record in actual work: check an AI tool, ask for disclosure, map vendor controls, build an evidence pack, or prepare a deployment review.
Check. Disclose. Map. Assess.
Four jobs cover most of what teams need to do with the record and the standard.
Check what your AI tools do with data.
Look up training reuse, retention, and opt-outs across the tools your team already uses.
Check tools you use →Publish an AI System Disclosure.
State what your systems do with data and decisions in a public, linkable disclosure.
Publish disclosure →Map vendors to the controls they cover.
Turn the standard into working controls for your stack, and find the gaps that stay yours.
Map a vendor →Run the readiness check on a live system.
Score a deployment against the PSF controls and get a public, citable readiness record.
Run readiness check →Inspect what AI products and providers actually say, and when it changes.
Check the AI Tools You Use
Select the AI products you use and get a plain-language summary of what those disclosures say about training on your data.
Run the check →AI Data Use Index
See what major AI products publicly say about training on user data, opt-outs, retention, and what remains unclear.
Open the index →AI Policy Change Watch
Track fixed monthly editions when reviewed AI providers materially change what they say about training use, opt-outs, retention, or human review.
Open change watch →Publish the basic AI facts people deserve, or ask an organisation to.
AI System Disclosure
Publish a public, linkable disclosure of what an AI system does: owner, purpose, data boundary, human route, and incident process.
Publish disclosure →Ask an Organisation About AI
Generate a plain-language request asking an employer, school, public body, or business to publish an AI System Disclosure.
Generate request →Request a Clearer Disclosure
Generate a serious provider email, public post, or buyer question set when the public answer is still fragmented.
Generate request →Turn PSF controls into working artefacts for your stack, vendors, and policies.
AI Vendor Control Mapper
Map vendor claims, integrations, and data flows to PSF controls, then generate procurement questions and a control-map report.
Map a vendor →AI Control Template Library
Copy-ready PSF control artifacts for input boundaries, output validation, data handling, observability, deployment gates, oversight, tool permissions, and provider fallback planning.
Open templates →AI Policy Templates
Free copy-paste AI policies for your organisation: acceptable use, data governance, incident response, and vendor assessment. Written by practitioners, not lawyers.
Get the templates →AI Vendor Assessment Checklist
Questions to ask before approving an LLM API, agent platform, observability tool, vector database, or automation provider for production use.
Assess a vendor →Production AI Deployment Checklist
A practical pre-deployment checklist aligned to the PSF. Use it before you go live with any AI system.
View checklist →Score live systems against the controls and turn results into reviewable evidence.
AI Adoption Guide for Companies
Place your organisation across five stages from gated access to AI-native operations, then identify the capabilities and guardrails required to move safely.
Find your stage →Production AI Deployment Guide
A step-by-step Australian enterprise path with Microsoft Foundry and Amazon Bedrock implementation options and a governed Finance and ERP example.
Follow the production path →Five-Year Enterprise Automation Roadmap
Sequence governance, cyber, data, platform, workforce, delivery, and value from the first 90 days to selective AI-native operations.
Plan the five-year path →AI Agent Readiness Check
Score a live agent deployment against the PSF controls and publish a citable public readiness report.
Run readiness check →Evidence Pack Builder
Turn readiness results and control checks into structured artifacts that survive procurement, audit, and internal review.
Build evidence pack →PAI Studio / WorkflowOS
Design PSF-mapped AI workflows in the browser and export them as deployment evidence. Free, open source, bring your own key.
Open Studio →AI Incident Response Playbook
A PSF-aligned operating rhythm for containing, assessing, remediating, and learning from AI failures and near-misses.
Read playbook →How to safely use AI in your organisation
A plain-language guide for executives and senior managers. Six questions to ask, common mistakes to avoid, and a practical governance roadmap.
Read the guide →Every tool maps back to the open standard. Read the PSF to see the controls these artefacts implement, or inspect how they show up in the public record.
Keep your AI map current
Tool policy changes, new incident records, disclosure signals, and practical next steps. Public evidence, plain English, no hype.