Higher Education

AI workflows built around academic work.

The work starts with what faculty and institutions already need to do. Build courses, design assessments, conduct research, manage evidence, and preserve the judgment those tasks require. AI is added where it improves the process, with the workflow built so the people using it can continue running it.

What the work covers

Three places to begin.

Every institution has its own rules, technology, access limits, and data restrictions. The workflow has to fit those conditions from the beginning.

i
Courses and assessment

Build materials and assessments that can be reused.

Course materials, individualized assignments, assessment design, and accessibility can be built into repeatable workflows. The aim is to improve the process behind the materials, not simply produce another set of documents.

ii
Research workflows

Reduce repetitive research work without weakening the research.

Literature organization, source verification, citation checking, data handling, and reproducibility can all benefit from better workflows. The goal is to reduce repetitive work while keeping research design, interpretation, and verification with the researcher.

iii
Handoff and adoption

Build a system your people can run.

Training, documentation, and handoff are part of the work. Faculty or staff should understand what the workflow does, where its limits are, and how to keep using and improving it after the engagement ends.

Why this is different

Built from teaching and research in practice.

These systems grew out of Minuci's own work as an economist and university professor. He uses AI in course development, assessment, research organization, data work, source verification, and other parts of the job where the process can be improved without handing over the judgment.

That experience changes how the workflow is designed. Academic work has deadlines, accessibility requirements, privacy and data restrictions, changing course needs, and research that has to withstand review. A useful system has to work under those conditions.

The objective is also clear. Faculty and students should still be able to verify the evidence, explain the reasoning, and defend the conclusion. A workflow is useful when it supports those abilities rather than replacing them.

Start with one part of the work.

It could be course preparation, a research workflow that is difficult to reproduce, or an assessment process that becomes harder as enrollment grows. Send a short description of the problem, or bring it to a free 20-minute introductory call.