Free, practical resources for practitioners and organisations deploying AI responsibly. No registration required.
Templates reduce friction, but the sale happens when a buyer, board, client, or team can see what proof comes next.
If the system is already touching customers, staff, or operational decisions, use the resources to prepare evidence and start a DSA scope.
Scope a DSA →Use the policy, disclosure, vendor, and control tools as the backbone of a client-ready AI governance service.
Get MSP launch pack →Pair the templates with foundation credentials so the team understands the controls they are being asked to follow.
Plan team rollout →Read the PSF, take AIDA, and use the tools before paying for anything more formal.
Start free AIDA →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 →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 →The PAI standard for production AI deployment — eight domains covering input governance, output safety, observability, access control, human oversight, data governance, incident response, and vendor resilience.
View the framework →A practical pre-deployment checklist aligned to the PSF. Use it before you go live with any AI system.
View checklist →See what major AI products publicly say about training on user data, opt-outs, retention, and what remains unclear.
Open the index →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 →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 →Generate a serious provider email, public post, or buyer question set when the public answer is still fragmented.
Generate request →Generate a plain-language request asking an employer, school, public body, or business to publish an AI System Disclosure.
Generate request →Copy-ready PSF control artifacts for input boundaries, output validation, data handling, observability, deployment gates, oversight, tool permissions, and provider fallback planning.
Open templates →Questions to ask before approving an LLM API, agent platform, observability tool, vector database, or automation provider for production use.
Assess a vendor →Map vendor claims, integrations, and data flows to PSF controls, then generate procurement questions and a control-map report.
Map a vendor →A PSF-aligned operating rhythm for containing, assessing, remediating, and learning from AI failures and near-misses.
Read playbook →PSF updates, deployment checks, failure patterns, and proof paths for practitioners, MSPs, and teams who need AI work to survive scrutiny. No hype.