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More time for teaching and research.

Recognition, re-registration, accreditation, funds requests: neuland.ai HUB agents read campus management, regulations and project accounts, for example, and submit reasoning, a reply or an overview as a draft.

neuland.ai HUB · Examination Office

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Application AN-2026-1187: can the course Data Analytics for Business from the University of Porto be recognized for the Business Analytics module in the Master's in Business Informatics?

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  • Campus management · Application AN-2026-1187read
  • Document management · Course description and transcript, Portoread
  • Document management · Module handbook MA Business Informatics, module WI-M07read
  • Examination administration · Earlier resolutions on this courseread
  • Document management · Draft reasoningDraft

Proposal: recognition. Four of five learning outcomes of WI-M07 are covered [1] [2]; the fifth, visualization with dashboards, is taught in module WI-M09 anyway. The difference of 0.5 ECTS (7.5 vs. 8) does not constitute a substantial difference [3]. The board recognized the same course on May 14, 2025 [4].

  • [1]Course_Description_Data_Analytics_Porto_2025.pdf · p. 2
  • [2]Module handbook MA Business Informatics 2024 · p. 31
  • [3]Transcript of Records, Porto · 7.5 ECTS
  • [4]Minutes examination board May 14, 2025 · Item 6

Draft the decision paper for the meeting on Oct 21.

  • Document management · Decision paper item 4.7Draft

The paper is ready: comparison of learning outcomes, reference to resolution PA 2025/042, proposal to recognize with 8 ECTS [1]. The examination board has to decide on Oct 21; the notice to the student is only issued after that.

  • [1]Resolution PA 2025/042 · Recognition for WI-M07
Decision paper item 4.7Meeting Oct 21, 2026 · WordDraft
  • done: Four of five learning outcomes covered
  • done: Earlier resolution PA 2025/042 referenced
  • open: Visualization: reference to module WI-M09
  • question: Awaiting the examination board's decision

The board makes the decision, not the agent.

For studies, quality and research

Agents for studies, accreditation and research, set up for your regulations.

Agents for studies, accreditation and research, set up for your regulations.

Student services, quality management and the research office start with one or more agents from the library and add examination regulations, state ordinance or funding guidelines as knowledge, without programming.

Student services

Student Guide Agent

Student services

Questions about the course of study, multilingual and in plain language: the Student Guide Agent answers from the examination regulations and the study plan and names the section and version. It passes individual cases on to student advising.

Accreditation

Accreditation Pre-Check Agent

Accreditation

Before the self-evaluation report: the Accreditation Pre-Check Agent checks the program concept against the formal criteria of your state ordinance, which you provide as knowledge, and flags what's missing. The reviewers assess the academic criteria later.

Third-party funding

Third-Party Funding Administration Agent

Third-party funding

Funds requests without returns: the Third-Party Funding Administration Agent guides you through account assignment, spending control and the funder's guidelines. The third-party funding office signs off the request.

Research data

Research Data Management Agent

Research data

The data management plan in the proposal: the Research Data Management Agent inventories an institute's research data and proposes metadata and DMP components. The repository gets datasets with metadata instead of a folder list.

Student services

Student Guide Agent

Questions about the course of study, multilingual and in plain language: the Student Guide Agent answers from the examination regulations and the study plan and names the section and version. It passes individual cases on to student advising.

Accreditation

Accreditation Pre-Check Agent

Before the self-evaluation report: the Accreditation Pre-Check Agent checks the program concept against the formal criteria of your state ordinance, which you provide as knowledge, and flags what's missing. The reviewers assess the academic criteria later.

Third-party funding

Third-Party Funding Administration Agent

Funds requests without returns: the Third-Party Funding Administration Agent guides you through account assignment, spending control and the funder's guidelines. The third-party funding office signs off the request.

Research data

Research Data Management Agent

The data management plan in the proposal: the Research Data Management Agent inventories an institute's research data and proposes metadata and DMP components. The repository gets datasets with metadata instead of a folder list.

Student services

Student Guide Agent

Questions about the course of study, multilingual and in plain language: the Student Guide Agent answers from the examination regulations and the study plan and names the section and version. It passes individual cases on to student advising.

Accreditation

Accreditation Pre-Check Agent

Before the self-evaluation report: the Accreditation Pre-Check Agent checks the program concept against the formal criteria of your state ordinance, which you provide as knowledge, and flags what's missing. The reviewers assess the academic criteria later.

Third-party funding

Third-Party Funding Administration Agent

Funds requests without returns: the Third-Party Funding Administration Agent guides you through account assignment, spending control and the funder's guidelines. The third-party funding office signs off the request.

Research data

Research Data Management Agent

The data management plan in the proposal: the Research Data Management Agent inventories an institute's research data and proposes metadata and DMP components. The repository gets datasets with metadata instead of a folder list.

Example · What's on the board's table

The decision paper the agent drafts: reasoning, not a course description.

The decision paper the agent drafts: reasoning, not a course description.

Under the Lisbon Recognition Convention, credits are recognized unless the university proves a substantial difference. The paper answers exactly this question: learning outcomes side by side, earlier resolution, proposal. The examination board has to decide.

Decision_paper_AN‑2026‑1187.docx
Draft

Decision paper item 4.7 · Application AN‑2026‑1187 · Meeting Oct 21, 2026

Application: recognition of Data Analytics for Business (Porto, 7.5 ECTS according to the Transcript of Records) for module WI-M07 Business Analytics (8 ECTS).

Learning outcomes: four of five learning outcomes of the module are covered [1]. Visualization with dashboards is not covered; it is taught in module WI-M09 anyway. The difference of 0.5 ECTS does not constitute a substantial difference.

Grade: 16 of 20 points, converted to 2.2 using the modified Bavarian formula.

No substantial difference can be established. The board recognized the same course with resolution PA 2025/042 [2].

Proposal: recognition with 8 ECTS.

[1]Module handbook MA WI 2024 · p. 31 · Course Description p. 2
[2]Minutes of May 14, 2025 · Item 6
DraftDecision at the meeting on Oct 21

If the board decides differently, its resolution becomes the reference for the next application.

Directly from campus management

The agent reads directly in campus management.

Nobody uploads the application a second time.

The agent reads directly in campus management.

Nobody uploads the application a second time.

The agent reads the transcript and course description where the student submitted them: in campus management. Ready-made connectors exist for SharePoint, Outlook, Teams and Nextcloud, for example; we connect the learning platform, DMS and other systems via their interfaces. It files the finished paper in the DMS only after your approval.

Data from Campus management, Learning platform, DMS, SharePoint, Nextcloud etc. flows through neuland.ai HUB to DMS, Outlook, Slack, Website etc.

Ready in the Agent Library

Ready-made agents for universities and higher education.

Each takes on one defined task, from application to research report.

Ready-made agents for universities and higher education.

Each takes on one defined task, from application to research report.

From student services to research: eight of dozens of agents for education and research.

Credit Recognition Agent

55%

faster processing

Checks academic credits earned abroad and drafts the reasoning for the examination board.

Education

Examination Office, International Office

Student Guide Agent

up to 60%

fewer first-level inquiries

Answers questions about the course of study in several languages and in plain language.

Education

Registrar's Office, student advising

Accreditation Pre-Check Agent

50%

fewer revisions

Checks program concepts against the formal criteria before the self-evaluation report.

Education

Quality management, Dean of Studies

Third-Party Funding Administration Agent

50%

less administrative effort

Guides you through account assignment, spending control and funding guidelines.

Education

Institute offices, Third-Party Funding Office

Research Reporting Agent

70%

less reporting effort

Aggregates research and third-party funding data in a structured way.

Education

Research office, management

Research Data Management Agent

60%

less search effort

Inventories research data and proposes metadata and DMP components.

Education

Research data management, institutes, library

Student Communication Agent

60%

faster processing

Automates structured communication with students.

Education

Student services, administrative office

Student Admissions Agent

50%

faster processing

Automates application and admission processes in a structured way.

Education

Registrar's Office, admissions

Figures are based on comparable projects and are not a guarantee.

Who sees which student data

Student data is visible only to the office that manages it.

Student data is visible only to the office that manages it.

Admins assign permissions per faculty, institution and role; within these permissions, teaching staff, administration and research work freely.

Grade lists

Never entire cohorts

Never entire cohorts

The Credit Recognition Agent reads module handbooks, resolutions and the one application, not the grade lists of entire cohorts. This is set per agent.

Permissions

Per faculty and role

Per faculty and role

Registrar's Office, research office and faculties are separated by granular permissions; tenant isolation applies between organizations.

Log

Every comparison

Every comparison

Every tool call the Credit Recognition Agent makes is in the log with arguments, response and duration, verifiable for every appeal against a decision.

Documentation

ISO 27001, DPA

ISO 27001, DPA

ISMS certified to ISO 27001, data processing agreement (DPA) under Art. 28 GDPR and documented TOMs, ready for your data protection officer.

DPA and TOMs are available for download for your record of processing activities.

Visit the Trust Center

What universities ask before they start

Eight questions before the first application

Eight questions before the first application

Does the Credit Recognition Agent fall under the high-risk rules of the EU AI Act?

Annex III No. 3 lists AI for evaluating learning outcomes as high-risk; Art. 6(3) exempts preparatory tasks under certain conditions. The Credit Recognition Agent prepares: it compares learning outcomes and drafts the paper; the examination board decides, and the Examination Office sends the notice. Your university assesses how your use case is classified.

Does the Credit Recognition Agent fall under the high-risk rules of the EU AI Act?

Annex III No. 3 lists AI for evaluating learning outcomes as high-risk; Art. 6(3) exempts preparatory tasks under certain conditions. The Credit Recognition Agent prepares: it compares learning outcomes and drafts the paper; the examination board decides, and the Examination Office sends the notice. Your university assesses how your use case is classified.

Do other faculties see our grade lists, and does a language model learn from them?

No. Permissions apply per faculty and role: each faculty sees its own grade lists, not anyone else's. The neuland.ai HUB processes grades, applications and research data in EU data centers or in your university's data center, your choice. They are never used to train language models.

Do other faculties see our grade lists, and does a language model learn from them?

No. Permissions apply per faculty and role: each faculty sees its own grade lists, not anyone else's. The neuland.ai HUB processes grades, applications and research data in EU data centers or in your university's data center, your choice. They are never used to train language models.

Does the agent need an export from campus management?

No. The agent reads the application, transcript and course description directly in the campus management system, connected as an additional service via its API or MCP. Sign-in uses your existing identity provider, and your faculties’ permissions continue to apply.

Does the agent need an export from campus management?

No. The agent reads the application, transcript and course description directly in the campus management system, connected as an additional service via its API or MCP. Sign-in uses your existing identity provider, and your faculties’ permissions continue to apply.

Does the staff council have to approve?

Clarify that with them before you start; the groundwork is ready: the Credit Recognition Agent prepares decisions on applications, not on employees. The neuland.ai HUB logs access per role; you decide together with the staff council and data protection which roles may evaluate these logs.

Does the staff council have to approve?

Clarify that with them before you start; the groundwork is ready: the Credit Recognition Agent prepares decisions on applications, not on employees. The neuland.ai HUB logs access per role; you decide together with the staff council and data protection which roles may evaluate these logs.

Can teaching staff and students use the neuland.ai HUB too?

Yes. Admins define per role which agents teaching staff and students see: the Student Guide Agent for everyone, for example, the Credit Recognition Agent only for the Examination Office. Chairs share their own agents with their team or the whole university.

Can teaching staff and students use the neuland.ai HUB too?

Yes. Admins define per role which agents teaching staff and students see: the Student Guide Agent for everyone, for example, the Credit Recognition Agent only for the Examination Office. Chairs share their own agents with their team or the whole university.

What does the neuland.ai HUB cost?

After two free test weeks, pilot and regular operation follow at fixed prices, plus a one-time onboarding fee. We prepare the offer based on your use case, details in the pricing overview.

What does the neuland.ai HUB cost?

After two free test weeks, pilot and regular operation follow at fixed prices, plus a one-time onboarding fee. We prepare the offer based on your use case, details in the pricing overview.

Is there training for teaching staff and administration?

Yes, the neuland.ai Academy offers two-day workshops, on AI strategy for example, and a modular program running six months; each format delivers, among other things, your own finished AI agent. The “AI Manager” course concludes with a certificate from eco e.V., and anyone introducing the neuland.ai HUB trains directly in it.

Is there training for teaching staff and administration?

Yes, the neuland.ai Academy offers two-day workshops, on AI strategy for example, and a modular program running six months; each format delivers, among other things, your own finished AI agent. The “AI Manager” course concludes with a certificate from eco e.V., and anyone introducing the neuland.ai HUB trains directly in it.

How many ready-made agents are there for universities and higher education?

The Agent Library shows dozens of agents for this industry, from student services to research. Each agent states its task and an efficiency figure from the library; these are figures from the library, not a guarantee. You adopt one or more agents and adapt instructions and knowledge to your institution.

How many ready-made agents are there for universities and higher education?

The Agent Library shows dozens of agents for this industry, from student services to research. Each agent states its task and an efficiency figure from the library; these are figures from the library, not a guarantee. You adopt one or more agents and adapt instructions and knowledge to your institution.

The first paper is ready before the next meeting.

Your last resolution is the reference.

Bring a module handbook, plus an earlier resolution and an application, both anonymized. In the neuland.ai HUB you see which paper the Credit Recognition Agent drafts from them.

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