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Research overview

Three tracks, architecture and agenda

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Methodology

Operational standards and validation

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Preprints, software, identifiers

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Research ethics

Fundamental rights and compliance

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Code, data, citation, open science

Collaboration & applications

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Collaborations in the public sector

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Protecting public spaces

Track B — rights-preserving early warning

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zensation

Research

🔬Research overview📐Methodology📄Publications⚖️Research ethics🧰Resources

Collaboration & applications

🏛️Public sector & funding🧭Adopt AI🛡️Protecting public spaces⚙️Technology
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Public sector & funding

Research collaboration with the public sector

We address security and law-enforcement authorities, federal and state ministries, and public research bodies with an interest in early-warning research in public spaces — under an explicitly fundamental-rights-compliant architecture.

Status note

This page addresses research, funding, and cooperation inquiries. The research is currently self-funded without external third-party funding; any third-party funding or consortium contributions acquired are disclosed publicly upon acceptance. Maturity is at the research-and-validation stage; a pilot together with user authorities is the intended next step. Operational deployment of security software is not the subject of this page.

Capacity to deliver

What this research already demonstrates

Before any funding or consortium decision comes the question of delivery capacity. This research is run by an independent, self-funded lab — and can point to a solid track record already in production.

Operational capacity

The same cognitive architecture we publish runs in production systems: ZenAI as a self-hosted knowledge-work platform and ZenBrain as an open-source core on npm. 11,589 automated tests and an open-access preprint with replication material show that the research becomes working, tested software.

Financial standing

The research is run throughout self-funded without external grants — carried by a registered sole proprietorship (DUNS 317163443). This independence allows a dependable own contribution within consortia; any third-party funding or consortium contributions acquired are disclosed publicly upon acceptance.

Impact pathway

The intended path runs from the research prototype (CrowdGuard) through a joint pilot with user authorities and external validation (notified-body pre-assessment, legal opinions) to transfer. The fundamental-rights-preserving civil-liberties architecture is the differentiator here — scientifically and in regulatory terms — and a source of European added value: security research that is deployable under EU law at all.

Consortium fit

Into a consortium the lab brings methodological rigour, a working prototype, production engineering, and persistent identifiers with pre-registration. Its natural role is the research-and-technology component — alongside user authorities as end users and a university or institute in the host role.

The evidence in detail: The principal investigator's background · Technology in production

What we offer

Research offerings for the public sector

Research collaboration

Joint research projects on concrete methodological questions: selection and annotation methodology, three-outlier validation, construct validity, inter-rater reliability (target: Cohen's κ ≥ 0.61).

Consortium partnership

Participation in consortium proposals for BMBF SIFO, Horizon Europe Cluster 3 (Civil Security for Society) and national funding lines. Public authorities are welcome as end-user components.

Data access via research clause

Structured data requests processable under research clauses (GDPR Art. 89 in conjunction with § 27 BDSG, plus sector-specific statutes where applicable) — with a prior MoU and a documented Data Protection Impact Assessment (DPIA).

Notified-body pre-assessment

Pre-assessment under AI Act Annex III (law enforcement). Outreach to TÜV SÜD, TÜV Rheinland and Bureau Veritas is in preparation; the architecture is designed for conformity (see Research Ethics). The deployer-side obligations — a Fundamental Rights Impact Assessment (Art. 27 AI Act) and registration in the EU database (Art. 49 AI Act) — are anticipated in the architecture.

Methodological advisory

Advisory on crowd-dynamics analysis, three-outlier model, civil-liberties architecture, demarcation from SPOT and the Berlin three-stage model, and reference-case methodology.

Trade-press contributions

Contributions in trade publications of the public sector (e.g. Behörden Spiegel) to communicate methodological content to practitioners.

What we do not do

Clear methodological demarcation

Authorities cooperating with us can rely on the following properties:

  • ✗No biometric identification of natural persons — no real-time remote identification system within the meaning of Art. 5(1)(h) AI Act
  • ✗No real-time person tracking or persistent tracking pipelines
  • ✗No predictive policing within the meaning of Art. 5(1)(d) AI Act
  • ✗No anomaly classification of political assemblies (Brokdorf safeguard)
  • ✗No deterministic person-level labels — exclusively calibrated probabilistic indications of statistical anomalies in collective dynamics

Funding and consortium paths

Pathways for joint proposals

Enquiries about third-party funding participation, consortium proposals, and commissioned research are actively considered. The pathways outlined below are the most natural entry points for collaboration.

BMBF SIFO — German Security Research Programme

Consortium build-up for the research line Safety in public spaces, with the application submitted via the project-management agency VDI Technologiezentrum (VDI TZ). Authority partners are structurally foreseen as end-user component; entry points exist via established innovation networks such as Fraunhofer SIRIOS and InnoBOSK. Outreach to research institutions in waves 2026/27.

Horizon Europe — Cluster 3: Civil Security for Society

Participation in European consortia in Disaster-Resilient Society, Protection of Critical Infrastructure, and Fighting Crime and Terrorism. Civil-liberties architecture as a methodological differentiator.

National funding (BMI, BMWK, ZIM)

Application-oriented research and development funding — in particular ZIM for SME research, BMI and BBK lines on civil protection and internal security.

Directly accessible funding routes

Programmes open directly to an independent research lab even without a university host — EIC (European Innovation Council), SPRIND (German Federal Agency for Disruptive Innovation), and the Cyberagentur (Agency for Innovation in Cybersecurity). These complement the consortium pathways in which a university or non-university institute takes on the host role.

Foundations and state programmes

Interdisciplinary security and fundamental-rights research via Carl Zeiss Foundation, Volkswagen Foundation, and federal state innovation programmes.

Enquiries about further funding or cooperation formats — for instance institutional research partnerships or directly funded commissioned research — are explicitly welcome.

Inquiry process

How an inquiry is structured

The following sequence has proven efficient and reliable for both sides — from initial contact to a joint pilot:

  1. 01

    Initial contact

    Brief outline of the authority's question, the proposed scope of collaboration, and (if applicable) funding path. Designation of contact persons.

  2. 02

    Methodological pre-briefing

    Confidential pre-briefing on research scope, civil-liberties architecture, and the methodological approach foreseen. This is also where the scope of a Data Protection Impact Assessment (DPIA) is set. NDA where needed.

  3. 03

    Memorandum of Understanding

    Written agreement on research goal, data access, role distribution, research-clause basis, publication rights, and endpoints. In parallel, the DPIA under Art. 35 GDPR and — where an authority is the user — the notified-body pre-assessment under AI Act Annex III are initiated.

  4. 04

    Proposal submission or direct engagement

    Joint funding proposal, consortium agreement, or — for smaller scope — direct research engagement.

  5. 05

    Joint pilot

    A pilot with the user authority within the agreed scope — bound to fundamental rights, with a human in the loop and documented endpoints. Operational deployment of security software remains reserved for a later, separately agreed phase.

Methodological standards

What our research is built on operationally

The first question before any cooperation concerns methodological robustness. The operational standards of our work are documented on a dedicated page: pre-registration of central documents via OpenTimestamps, replication material as a default part of every publication, external validation through peer review, notified-body pre-assessments and legal opinions, documented ablation studies, and data minimisation as a methodological decision. Funding bodies and research institutions will also find there the open methodological questions we name ourselves.

Go to the methodology page →

Legal and ethical framework

All cooperations are bound to fundamental rights

Prior to any operational phase, the documented framework applies: GDPR Art. 89 in conjunction with § 27 BDSG, AI Act (demarcation from Art. 5(1)(d), design for high-risk requirements under Annex III), freedom of assembly (BVerfGE 69, 315), and data minimisation. A Data Protection Impact Assessment under Art. 35 GDPR is conducted.

To research ethics →

Contact for the public sector

Send an inquiry

For research and consortium inquiries from authorities, ministries, and public research bodies, please get in touch at the address below. Initial inquiries are typically answered within ten working days.

Send public-sector inquiry →

More from this research

Related pages

Core and application fields, on a shared ethics foundation.

  • Research →Three tracks: cognitive architectures, safety in public spaces, applied AI.
  • Technology →ZenBrain in depth — 7 memory layers, algorithms, RAG pipeline, performance.
  • Adopt AI →A neutral roadmap for AI adoption — prioritisation, stage-gates, KPIs and EU AI Act / GDPR governance, with an interactive simulation.
  • Methodology →Pre-registration, reproducibility, external validation, data minimisation — operational standards in detail.
  • Publications →arXiv, Zenodo (DOI), software releases, open-access principles.
  • Resources →Code, replication material, BibTeX citation, licences, identifiers.
  • Research ethics →GDPR Art. 89, AI Act Art. 5, Brokdorf line. Eight mandatory corrections.
  • Principal Investigator →Profile, background, identifiers, contact paths.

© 2026 Alexander Bering / ZenSation Enterprise Solutions

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