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Trust Center

Responsible AI

Transparency, human oversight, fairness, privacy and governance: the principles Univerx builds AI on, and the controls that put them to work in AI agents, Univerx Assist and Semantic².

Designed for · principles & controlsUpdated on 2 November 2026

At a glance

  1. Designed for

    The platform is built toward the requirement. Evidence such as an attestation does not exist yet – we name it as soon as it does.

  2. On request

    The documents exist. You receive them for your review through the contact form.

  3. Available

    Met and evidenced. We assign this level only once the evidence exists.

Documents on request

No documents are listed for this topic. We answer the questions from your questionnaire in conversation.

#Why principles are not enough

Almost every provider has AI principles. What counts is whether they reach the product: as a setting nobody can forget, as a log anyone can read, as an approval someone is accountable for.

That is why Univerx describes each principle together with the control that implements it. Where a control is configurable, we say so. Where it is a goal, we say that too.

#Five principles, five controls

PrincipleControl in the product
TransparencyAI identifies itself as AI in dialogue; suggestions for agents are recognisable as suggestions.
Human oversightHandover to a person at any time; suggestions and findings are accepted or rejected by people.
FairnessAnalytics are explainable; performance analytics are built to be agreed with works councils.
PrivacyRole rights, data held in the EU, retention periods per data type.
GovernanceCentral approval and versioning of models and prompts; a log of every action.

#How the controls apply

#AI agents

AI agents resolve requests on their own and act in connected business systems while doing so. They identify themselves as AI, hand over to a person with context at any time and log every action.

#Univerx Assist

Univerx Assist suggests, the agent decides. Summaries and reply suggestions rely on the approved knowledge base, not on a model's general knowledge of the world.

A grounded answer with its source from the knowledge base. Sample view.

#Semantic²

Semantic² reads documents and reports discrepancies as findings in euros, with rule and source. No finding is booked automatically. A person makes every decision, and it is logged.

#Governance day to day

Governance is not a committee that meets once a year. It is a process every change to an AI goes through, from first draft to rollback.

  1. Design. A team builds or changes a flow in Agent Studio, without code.
  2. Review. The team checks the flow against examples before it reaches customers.
  3. Approve. An accountable person approves model and prompt; the version is stored.
  4. Observe. Conversation analytics and logs show how the flow performs in operation.
  5. Roll back. If needed, an earlier version is restored.

#Read on

How the principles relate to the duties of the AI Act is set out on EU AI Act. The guide Introducing AI agents responsibly turns the points to settle before launch into a checklist.

Why a well-kept knowledge base is the foundation of grounded answers is the subject of Grounded answers. The product page Responsible AI gives an overview of the features.

Products

Where the topic applies.

The product families this topic matters most for.

  • Univerx AI

    AI that resolves requests and backs up people.

    • AI Act
    • DSGVO
    • EU
    Learn more
  • Univerx Trust Center

    Security and regulation as a design principle, not an appendix.

    • DSGVO
    • EU
    • AI Act
    • BSI C5
    • eIDAS
    • NIS2
    • DORA
    • BFSG
    Learn more

Trust & Europe

Every topic in the trust center.

Every topic carries a status. It tells you what is a design goal, which documents you can request and what is evidenced today.

Trust center topics with status, affected product families and number of documents on request
TopicStatus
GDPROn request
Data residency & hosting in GermanyDesigned for · German hosting planned
EU AI ActDesigned for
BSI C5Designed for · goal, no attestation
eIDAS & online IDDesigned for
NIS2Designed for
DORADesigned for
European Accessibility ActDesigned for · WCAG 2.1 AA as a goal
Responsible AIDesigned for · principles & controls
Security & availabilityDesigned for
United States: HIPAA, PCI DSS, SOC 2, TCPA, CCPADesigned for

Frequently asked questions

Can an AI be changed without approval?

Models and prompts are approved and versioned centrally. A new version only goes live after approval, and an earlier one can be restored.

Where do generative AI answers come from?

From your approved knowledge base. Generative answers rely on sources you maintain. If the AI finds no reliable source, it is designed to say so or hand over to a person.

How do you deal with bias?

Fairness is a principle, not a promise. For your use case we agree how you will spot bias, for example through samples per language or customer group. And where decisions affect people, people decide.

How do the principles relate to the EU AI Act?

They point in the same direction but do not replace a legal assessment. The EU AI Act page describes what the regulation requires and what Univerx is designed for.

See Univerx on your own example.

In a demo we show the platform along your channels and requests, from AI agents to video, workforce scheduling and analytics.

Online, in German or English, with no preparation on your side.