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 value
Practical review notes for AI Compliance Kit
The page should help a team make a practical AI governance decision, not simply repeat regulation language. This page is written to help visitors understand how the site is maintained, with concrete checks they can apply before relying on the result.
What to decide first
Start by naming the real user problem, the decision owner, and the final artifact needed after reading this page.
What to keep as evidence
Useful outputs include a saved classification, an owner, an evidence list, a disclosure draft, and a date for the next review. Visitors should be able to copy, export, save, or repeat the workflow later instead of treating the page as a one-time explanation.
What not to overclaim
The tools are self-assessment aids. A higher-stakes launch still needs internal sign-off and, where appropriate, professional legal review. The page avoids fake certainty, hidden uploads, broken next steps, and generic claims that do not help someone complete a real task.
Recommended next step
After reading this page, open the most relevant tool, run a realistic example, and compare the output with your actual requirement. If the result will be used publicly, save the generated artifact and keep a separate note explaining why you accepted it.
Open the main workflow tool or browse the example library for a complete use case.
Worked examples
See the tools in real workflows
The example library shows complete use cases with inputs, decisions, outputs, and limitations. It gives visitors a clearer reason to stay, compare, and use more than one page.
Customer Support Chatbot Disclosure Review Example
A practical review example for teams checking whether an AI customer support chatbot needs a clear disclosure notice and operating record.
Open exampleResume Screening AI Review Record Example
A high-risk AI review example for hiring teams documenting a resume screening or candidate ranking system before launch.
Open exampleAI Vendor Due Diligence File Example
A due diligence file example for buyers collecting security, data, model, and compliance evidence from an AI vendor.
Open exampleDetailed operating notes
How to evaluate AI Compliance Kit
This section turns the page into a practical AI compliance workflow. It gives the reader a way to prepare inputs, judge the output, and keep a useful record instead of leaving with a shallow summary.
1. Prepare the real requirement
Before using this page, identify the AI system, the user group affected by it, the decision it supports, and the person who owns the review. The more precise the requirement is, the easier it is to decide whether the generated result is ready to use or needs another pass.
For a real project, write the requirement in one sentence and keep it next to the result. That simple note helps future reviewers understand why a specific setting, wording, rule, file format, or checklist item was chosen.
2. Review the output carefully
The expected outcome is a review record, inventory entry, disclosure draft, policy note, or vendor evidence request. A useful result should be specific enough that another person can inspect it, repeat it, or compare it with the original requirement.
After generating an output, save the assumptions used for classification, because later policy, vendor, or product changes can alter the risk profile. If the output is vague, missing a key field, or does not match the destination requirement, revise the inputs and run the workflow again.
3. Avoid the common failure
The most common mistake is treating a tool result as legal clearance without recording the facts, limitations, and human approval behind the decision. This site is designed to reduce that risk by keeping tool actions visible and by linking guides, scenarios, and examples back to a concrete workflow.
When the page involves public publishing, compliance, or access rules, keep the final result separate from the draft. That makes it easier to rollback, correct, or explain the decision later.
Quality checklist before you leave
- Confirm that the page you used matches the actual situation, not just a similar title.
- Check every generated recommendation, file, rule, or notice against the requirement you wrote down first.
- Save a copy of the final output with the date, source page, and owner of the decision.
- Use the example library when you need to see how the same workflow behaves in a complete real-world case.
- Return to the main workflow when the requirement changes, instead of editing old output by guesswork.