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Research overview

Three tracks, architecture and agenda

Publications

Preprints, software, identifiers

Methodology

Operational standards and validation

Research ethics

Fundamental rights and compliance

Resources

Code, data, citation, open science

Adopt AI

Neutral roadmap & interactive simulation

Public sector & funding

Collaborations in the public sector

Protecting public spaces

Track B — rights-preserving early warning

Technology

The architecture behind every application

Playground

Run the open memory core live

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Research overviewPublicationsMethodologyResearch ethicsResources
Adopt AIPublic sector & fundingProtecting public spacesTechnologyPlayground
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Method

How to adopt AI the right way

Most AI initiatives fail not on technology but on what you pick and in which order — and on bolting AI onto old processes instead of rethinking the process itself. Our approach is deliberately lean: a fast assessment, the 2–3 most valuable processes first, clear stage-gates and measurable KPIs — tailored to size, maturity, budget and time.

Generate your AI roadmap in ~1 min →

Free · no sign-up · runs in your browser · neutral orientation

The approach in five steps

1

Assessment

Throw in documents, key facts and the goal — or a kickoff conversation. We capture size, maturity, systems and constraints (budget, time, risk).

2

Prioritise

Every use case is scored by value × feasibility × risk and grouped into waves — quick wins first, chosen so the first step lays the reusable foundation for scaling (not a dead-end pilot).

3

Pilot

Wave 1 with 2–3 initiatives. Clear stage-gates: pilot (useful in ≥ 80 % of cases) → validation → scale-up.

4

Measure & scale

Each initiative gets KPIs with a baseline and target. We only roll out once value is proven.

5

Governance & enablement

EU AI Act classification, GDPR and training are built in. Success is 70 % about people — sponsor, champions, clear communication. And people use AI markedly more when they stay in control (the human decides, the AI suggests).

For companies and public bodies

  • EU AI Act risk classification per use case (incl. FRIA flag)
  • GDPR data sovereignty — fully local (local-only) on request
  • BSI C5-ready, audit trail and traceable recommendations

EU AI Act: what the architecture supports

From 2 August 2026 the AI Act’s core obligations apply. Whether a system is high-risk and how it is operated compliantly is the operator’s call — the architecture provides the foundation. What ZenSation brings to it:

Transparency (Art. 13)

Open-source core, documented memory operations — traceable, not a black box.

Record-keeping & logging (Art. 12)

Every store and recall operation is loggable and auditable.

Human oversight (Art. 14)

The human decides, the system suggests — control stays with you.

Data governance (Art. 10)

Self-hosting, data minimisation and access control are configurable; data never leaves your house.

Important: classifying and conformity-assessing a specific system remains the operator’s responsibility. ZenSation provides the architectural foundation — not a certificate.

GDPR, EU AI Act & sovereignty — frequently asked

Is ZenSation GDPR-compliant?

Yes — the architecture is built for it. ZenSation runs self-hosted in your own or EU infrastructure, so personal data never leaves your house; every store and recall operation is traceable, and data minimisation and access control are configurable. The standard variant already provides this foundation — for specific requirements we set everything up exactly to your needs.

Does our data leave the company?

No. Models and memory run in your infrastructure (on-premise or an EU cloud of your choice), with no transfer to third parties. This removes the most sensitive data-protection question — data leaving the building — architecturally, from the outset.

Can it be adapted to public-sector requirements?

Yes, up to authority level. Because the architecture is modular, it can be defined precisely against regulatory and organisational requirements — from the standard variant to specific public-sector demands. We set up deep specialisations exactly as the given framework requires.

How is co-determination handled (works council / staff council)?

Co-determination is considered from the start. Full traceability, configurable access control and clear purpose limitation make it straightforward to meet works-council or staff-council requirements — no covert monitoring. We agree the concrete arrangement with your council.

Is the standard variant enough, or do we need a custom setup?

The standard variant already provides the GDPR foundation — self-hosted, auditable, data-minimising. For deeper or public-sector requirements we configure every layer as needed, without breaking the architecture, because modularity is the foundation.

Does it run in our existing tech stack?

Yes. As an open-source library (Apache 2.0), ZenSation runs in almost any stack — your own database (PostgreSQL/SQLite), your own LLM, your own infrastructure. No cloud lock-in, no vendor lock-in.

Is it “EU AI Act ready”?

The architecture supports core AI Act obligations: transparency through open source, traceability and logging of every operation, human oversight, and data governance through self-hosting. Classifying and conformity-assessing a specific system remains the operator’s responsibility — the architecture provides the foundation for it.

Interactive simulation: your AI roadmap

Try it — a few key facts are enough (or use an example). The simulation derives scope, modules, a prioritised roadmap with waves, gates and KPIs, plus a vendor-independent cost estimate. Meant as neutral orientation, not a quote.

Runs right in your browser, no sign-up.

The research behind it

Our method is grounded in ZenBrain technology and peer-reviewed research.

ZenBrain technology →Interactive companion visualization →The product behind it: ZenAI →Put it to work in your organization →
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