Privacy & Data Governance
How we treat data, minimize collection, and respect the people our systems serve.
Data practices
We treat the data entrusted to us—especially information about students, minors, and their wellbeing—as sensitive by default, and we design our handling around the principles that healthcare- and education-privacy frameworks are built on.
- Data minimization. We collect only what a task genuinely requires, and avoid accumulating sensitive data we don't need.
- Purpose limitation. Information provided for one purpose is not repurposed outside the terms under which it was shared.
- Access on a need-to-know basis. Sensitive data is designed to be available only to those with a legitimate role, consistent with institutional governance.
- Confidentiality as a baseline. We handle student and wellbeing-related information in line with the confidentiality principles that HIPAA- and FERPA-governed environments are built around.
- Respect for institutional control. Where we serve schools and districts, the institution remains the steward of its data; we operate under its governance.
This page describes our data-governance principles and intent, not a certification under any specific regulation.
Writer & manuscript confidentiality
Authors trust Remu with unpublished work—manuscripts, drafts, and creative material that represents their livelihood and intellectual property. We treat that trust as central to the product, not an afterthought.
- Your work stays yours. Authors retain ownership of the content they create and upload. Using Remu to assist with editorial review does not transfer rights in your work to us.
- Not used to train AI models. Manuscripts and content processed to provide editorial assistance are not used to train or improve AI models—not ours, and not our providers'. We work with enterprise-grade AI providers under terms that prohibit using customer content for model training.
- Processed to serve you, not to be mined. Author content is used to deliver the assessment and feedback you asked for—nothing more. It is not repurposed, sold, or shared to enhance any model or product.
- Limited access and retention. We design our workflows to minimize how much author content is exposed and how long it is retained, keeping data access scoped to what delivering the service actually requires.
- Provider standards we hold to. We reserve the right to work with different AI and infrastructure providers over time, and we select them for alignment with our security and data-protection expectations—including their handling of customer content.
This describes our confidentiality commitments and design intent for author content. Specific terms are governed by the applicable product terms of service.
Questions
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