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HermeneuticaHumanities AI

A studio for human-centered AI

Human inquiry. Thoughtful AI.

AI consulting and scholarly tools for the people who teach, read, and ask the difficult questions.

Step inside the workbench
The Hermeneutica workbench
Working preview · Sample texts

Reading Lab / $INQ-1-P1

On interpretation

An interpretation begins with attention. We return to a passage not only to find an answer, but to ask . The work of understanding .

Click a phrase to anchor it, then code it from the judgment rail.

Roles
Texts → Context → Evidence → Your interpretationOpen the external Workbench demo

Mark a phrase, code it, and write the note. The desk keeps your judgment in view. It does not call a live model.

Faculty-centered · Discipline-specific

Humanities programsTeaching & learning centersLibraries & scholarly partners

The system

Four rooms.
One reading desk.

Use the desk above. Mark a phrase, code it, and ask a role. The argument takes shape from what you keep.

Hermeneutica is a system for reading with the text still in front of you. One desk holds the passage. Four rooms keep the corpus, the close reading, the context, and the argument attached to that passage. Named review roles may propose a note. Faculty decide what remains.

1 · HERMES

Scriptorium

The corpus desk. Readings, catalog, and the works a course actually assigns — epic, tragedy, modern prose, or your own shelf.

2 · Lab

Reading Lab

Close reading with coded passages, a codebook, and notes that stay attached to the line you can point to.

3 · Clio

Clio Explorer

Questions of person, place, and circumstance. Context is investigated and checked, not filled in for you.

4 · Graph

Argument Graph

A question, a source anchor, and an interpretation. The connection stays visible so a reader can disagree.

On the desk

  • Readings
  • Codebook
  • Coded passages
  • Quick note
  • Cite
  • DAG
  • Executive summary
  • PDF archive

Six named review roles sit under the reading — Bibliographer, Hermeneutic Reader, Ideology & Discourse Critic, Clio Archivist, Graph Architect, and Academic Web Harvester. They propose. Faculty decide. Outputs stay inspectable: an executive summary, a PDF archive, and the coded passage a colleague can open.

Let’s begin

Bring a course.
A challenge. An idea.

We’ll start with where AI could help — and where it should not. Scope and pricing are defined after discovery.

Do we need to adopt the whole workbench?

No. Training, solution design, and implementation can be scoped separately. Start with the need, then choose the tools.

What about privacy and academic integrity?

Start with institutional policies and data boundaries. Agree on permitted data, provider settings, human review, and evaluation before piloting. Review compliance requirements with your institution.

Is the workbench above a live AI tool?

No. You can mark phrases, apply codes, write notes, and sketch an argument here, but nothing calls a live model. Passages are original samples. Role prompts are preset. Your work stays in this preview and resets when it reloads. Use the external demo links for the separate product demonstrations.