Classify the use case
Identify high-risk signals across employment, education, credit, biometric, critical infrastructure, healthcare, and public-sector use cases.
EU AI Act self-assessment
AI Compliance Kit
Find your AI risk level before it becomes a launch blocker. A practical classifier for builders, SaaS teams, agencies, and small businesses that need first-pass EU AI Act risk triage without reading hundreds of pages of legal text.
Built for the messy middle between “just an AI feature” and “we need legal review.”
Most small teams do not need a 90-page report on day one. They need a clear signal: what kind of AI system are we building, what could trigger high-risk obligations, and what should we document next?
Generate a checklist
Turn the result into a practical next-step checklist covering transparency, human oversight, logging, data governance, and specialist review.
Guidance with context
The tool is supported by explanatory guides, templates, source links, and clear disclaimers so the site is built around clear user workflows.
Start with a workflow, then use the right tool at each step.
This site is built around practical artifacts: inventories, risk snapshots, policies, disclosures, vendor questionnaires, literacy plans, and reports that teams can save.
AI Compliance Review Workflow
Generate a step-by-step review path across inventory, risk, policy, disclosure, vendor review, and literacy evidence.
AI Inventory Generator
Create an AI system inventory with owners, vendors, data types, risk signals, missing evidence, CSV, and reports.
EU AI Act Risk Classifier
A rules-based self-assessment for AI teams that need initial risk triage.
Article 50 Disclosure Generator
Generate AI transparency notices, HTML banners, and compliance-file notes.
AI Vendor Risk Questionnaire
Generate procurement questions, red flags, evidence requests, CSV, and review reports.
AI Policy Generator
Draft an internal AI acceptable use policy for approved tools, data boundaries, human review, and incidents.
AI Literacy Plan Generator
Create role-based AI literacy modules, evidence records, CSV schedules, and printable reports.
Prohibited AI Practices
A practical screening guide for use cases that may need to stop before launch.
Limited-Risk Transparency
When chatbots, assistants, and generated content need clear user notices.
High-Risk Checklist
A launch-readiness checklist for consequential AI systems.
AI Transparency Notice Template
A starter notice for chatbots, assistants, and generative AI features.
Documentation Template
A compact file structure for intended purpose, oversight, risk controls, and review notes.
High-Risk AI Systems
A plain-English guide to the categories that deserve deeper review.
EU AI Act Timeline
Key dates and practical planning checkpoints for 2026.
EU AI Act for US SaaS
Scope signals for non-EU teams selling, deploying, or processing AI outputs in Europe.
Find the checker that matches your AI product.
Scenario pages turn one broad compliance topic into focused search entries for chatbots, hiring tools, generative media, healthcare AI, education scoring, credit review, biometrics, and workplace monitoring.
Disclaimer: AI Compliance Kit provides initial self-assessment tools and educational content.
It does not provide legal advice, certification, or a guarantee of compliance.
practical AI compliance self-assessment
Practical notes for AI Compliance Kit
AI Compliance Kit | Free AI Compliance Tools is maintained for founders, product managers, compliance owners, agencies, and small teams building AI workflows who need AI governance workflow. The goal is to help visitors complete a real task and leave with an AI inventory, risk note, disclosure draft, vendor question set, policy outline, or review workflow report, not only read a generic summary.
Define the system
Start by naming the AI feature, users, decision impact, data categories, vendors, and the team member responsible for maintaining the review record.
Separate triage from advice
Use the generated output as first-pass operational triage. Legal, medical, hiring, credit, education, biometric, and public-sector uses still need specialist review.
Keep evidence
Save the output, assumptions, date, source links, and reviewer notes so the team can explain why a risk level, disclosure, or vendor question set was chosen.
Before relying on this page
- Review high-impact use cases manually.
- Keep policies and disclosures aligned with the real product behavior.
- Re-run the workflow when vendors, data, or user impact changes.
Review record
How to use AI Compliance Kit in an AI compliance file
A compliance tool is useful when it leaves a traceable record. The output should name the AI system, explain the assumptions, and show what the team still needs to verify with product, legal, security, or vendor owners.
Describe the real system
Record the feature name, user group, decision impact, data sources, vendor dependencies, and the human owner. A generic "chatbot" label is rarely enough. A hiring assistant, support summarizer, medical triage bot, and product recommender can have very different risk profiles even if they all use language models.
Separate signal from conclusion
Treat this page as first-pass triage. It can flag high-risk areas, transparency duties, missing evidence, and questions to ask a vendor. It should not be treated as legal approval, clinical advice, hiring approval, credit approval, or permission to launch without human review.
Save evidence and changes
Save the generated result with the date, reviewer, source links, and unresolved questions. Update the record when the model, data, users, product flow, vendor, or region changes. This keeps the site useful for actual operators rather than only being a static explanation page.
Evidence checklist
- Document what the AI system does and what it does not do.
- Record whether the system influences employment, education, credit, public benefits, healthcare, biometric identification, safety, or other high-impact outcomes.
- Keep vendor documentation, model notes, data descriptions, user notices, human oversight notes, and monitoring plans together.
- Re-run the review when the product behavior changes, not only when the law changes.
- Use specialist review for high-impact or regulated workflows before relying on any generated text.