Pilots, pricing, and privacy

Inline connects feedback to teaching. Students get short questions beside the passages they need to work on.

When they submit, professors can review the draft, earlier saved versions, and feedback together, then leave their own comments.

You can see how the work developed instead of receiving only a final essay.

Start with a course or teaching team, a term, and an approximate student count. com to discuss access and what to evaluate.

Participating professors invite students to Pro. Research participation is separate and optional.

Request professor access in the app. Once approved, create a class, add your assignments, and share the class link or code.

Students join with their own accounts and keep their drafts private until they submit.

Yes. Add your instructions, rubric, and context to the assignment. Students can read them beside their draft, and Inline uses that context for assignment feedback.

You set the expectations and make the grading decisions.

Yes. A submission includes the saved questions as well as the writing. You can review and rate Inline’s feedback, compare draft versions, and add your own comments beside the student’s text.

Those connections are planned. For now, users sign in to Inline and join a course through a class link or code.

A model tuned to your faculty’s feedback is also planned; today’s tutor uses assignment context with a shared model.

Drafts are stored in the student’s account and processed on infrastructure Inline controls.

Product drafts are never used to train models or sent to third-party AI services. Professors receive only the fixed course work students deliberately submit.

An administrative role does not give access to private writing. Authorized teaching members can read course submissions.

Broader writing-center dashboards are planned; they are not a current pilot feature.

The draft, every retained saved version, all saved feedback and Brainstorming questions, and recorded writing-activity totals.

Students preview the complete copy and its teaching recipients before submitting. Later edits remain private.

This history helps a professor discuss the writing process; it does not prove authorship or AI use.

No. It shows saved work and recorded activity so a professor can discuss how a draft developed. It does not give an AI-detection or cheating score.

Work done elsewhere may be missing, and a short history is not evidence of misconduct.

Review the app’s privacy terms, who can access submissions, retention rules, and the support students will need. com before a pilot so we can confirm what is supported.

Test the student and professor workflows with your accessibility team and the assistive tools your community uses.

We can discuss barriers and an alternative route for students who need one. Our website accessibility statement describes the checks completed on this site; it is not a certification of the app.

Students get feedback while they are writing. Professors get a course workspace that brings submitted drafts, revisions, and feedback together.

That gives a teaching team more to work with than the final essay alone, without asking students to assemble a separate record of their process.

Estimated institutional pricing is $10 to $16 per covered student per year, depending on the number of students.

Use the calculator for an estimate, then contact us to discuss the right scope for your institution.

No. Start with one course, a department, or a writing program. The calculator starts at 500 students for larger plans; that is not a minimum class size for a pilot.

Contact us about the students you want to include.

Through annual institutional licenses for student Pro access and professor course workspaces. Individual Free access remains part of that model.

Product drafts are never training data.

The current pilot involves seven professors teaching more than 150 students. That is pilot scope, not a count of active users or proof of learning gains.

We need to measure whether students make better revisions and whether professors find the feedback useful before claiming improved learning outcomes.

Look at whether students return to revise, whether the questions fit the assignment, and whether the revisions address the issues raised.

Ask professors and students what helped and what got in the way. Usage alone does not show better writing.

The connected course record: passage-level questions, saved draft versions, and professor review in one place.

A teaching team can follow how submitted work developed and judge the feedback against the revisions.

Inline’s value comes from making that useful in real courses, not from exclusive access to an AI model.