Sample report · excerpt · Lite Version

This is what a Lite Version evaluation can look like for a company.

This example uses the fictional Muster Maschinenbau GmbH to show the structure, value and next steps generated by the Lite Version. It is an excerpt - the complete Lite Version also includes editable files, templates and attachments.

Fictional company

Muster Maschinenbau GmbH

62/100

Status: first structures exist, but key evidence, supplier information and AI literacy documentation are still missing.

What the sample report immediately shows

  • which AI use cases are known
  • where personal data, customer data or business information may be involved
  • which supplier information is missing
  • whether AI literacy activities are documented
  • which questions should later be clarified with legal, data protection or compliance
  • which first actions are useful within 30, 60 and 90 days
4AI use cases
7open evidence items
9review fields
Starting point

Before the Lite Version: AI is used, but not centrally structured.

Muster Maschinenbau GmbH uses generative AI for sales texts, service summaries, technical documentation and internal research. Several teams already work productively with AI tools. At the same time, there is no central AI inventory, no consistent supplier overview and no documented AI literacy activity.

This is where the Lite Version starts: it does not create a final legal assessment, but an initial working structure.

The company receives

  • an initial AI system overview
  • a readiness score
  • a list of missing information
  • an evidence matrix
  • a supplier questionnaire
  • an AI literacy documentation template
  • a 30/60/90-day plan
  • questions for legal, data protection and compliance
Sample questions

Questions asked in the Lite process

The Lite Version does not require confidential document uploads. It first structures basic information that is often distributed across the organisation or not documented at all.

  • Which AI tools are currently used in which departments?
  • Are personal data, customer data or internal business information entered?
  • Is there already an AI policy or usage rules?
  • Is there a person responsible for AI governance?
  • Are training or awareness records available?
  • Are external AI suppliers used?
  • Is there any HR, recruiting, scoring, safety or product context?
  • Are decisions prepared or made automatically?
  • Is there human oversight?
  • Which supplier information is already available?
  • Which evidence is missing?
  • Which questions should later be clarified with legal, data protection or compliance?
Sample AI inventory light

Scattered tools become an initial AI inventory.

The table shows how the Lite Version structures AI use. The full customer version also includes exportable working data.

AI useDepartmentData relevanceControlOpen point
Sales text generationSalesCustomer and product information possiblehuman approvalAI usage rules missing
Service ticket summarisationCustomer servicepersonal data possiblepartial reviewsupplier information missing
Technical documentation supportEngineeringinternal business informationexpert reviewconfidentiality rules to check
Internal AI researchManagement / assistantmixed internal datanot consistenttraining and logging to clarify

Readiness profile of the sample company

The score is not a legal assessment. It shows how well the basics for a later review are prepared.

Readiness Score62/100first structure, but evidence and supplier information are missing

AI inventory

AI literacy

Governance

Data protection touchpoints

Supplier information

Evidence

Open evidence in the example

  • central AI inventory
  • internal AI policy or usage rules
  • AI literacy records
  • supplier information on data processing and training
  • responsible role or person for AI governance
  • process for approval, oversight and incidents
  • documentation of human oversight
Supplier questionnaire

What should be requested from AI suppliers

Many companies use external AI tools. The Lite Version therefore includes questions that can be addressed to suppliers, SaaS providers or model providers.

It asks, for example, about

  • data processing
  • training use
  • storage locations
  • security documents
  • technical documentation
  • contact person
  • model information
  • roles in the AI Act context
Evidence matrix

The sample report shows concrete follow-up requests, not only problems.

Evidence / informationStatus in exampleWhy it mattersNext step
AI inventorymissingBasis for role, risk and data reviewCapture AI systems in the light template
AI literacy recordnot documentedPreparation around Article 4 and internal awarenessStart 30-minute briefing
Supplier informationpartly unclearData, training, security and responsibilitiesSend supplier questionnaire
AI policynot availableUsage rules, approvals and boundariesAgree basic internal rules
Human oversightpartly availableImportant for AI-supported work processesDocument control points

Questions for legal, data protection and compliance

The Lite Version helps prepare later expert discussions. The sample report generates questions such as:

  • Which AI systems require deeper review first?
  • Which role does the company have per system: provider, deployer or both?
  • Which data may employees enter into external AI tools?
  • Which transparency or information duties may become relevant?
  • Which supplier information is indispensable for later review?
  • Are there high-risk indicators that require deeper analysis?

30/60/90-day plan

30 daysCollect AI systems, assign owners, send supplier questionnaire.
60 daysDocument AI literacy briefing, prepare AI policy, review data types.
90 daysClose open evidence gaps, set priorities, prepare Pro Version or specialist review.

The sample report is only an excerpt.

The full Lite Version also includes PDF, DOCX, HTML working version, CSV lists, source list, evidence documents and templates. It shows enough to understand the value without giving away the complete internal methodology.

199 €

incl. 19% German VAT where applicable

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