At HeinOnline, we recognize that introducing artificial intelligence into research workflows must be grounded in transparency, security, and trust. With the upcoming launch of AI Summaries, our first AI-powered feature, we want to be clear about how our infrastructure protects our users and their data.
100% In-House Infrastructure
All AI functionality within HeinOnline is built, trained, and maintained entirely by HeinOnline. We do not use external vendors, third-party APIs, or cloud connectors. This ensures we retain full control over both infrastructure and data protection at every step.
No User Data Processed or Stored
AI Summaries are generated from HeinOnline content within the Law Journal Library. No user data is collected, processed, transmitted, or stored to produce summaries. Researchers can be confident that their searches, personal information, and institutional data remain private and untouched by AI.
Passive, Pre-Processed Summaries
Unlike open-ended chatbots, AI Summaries are pre-processed in advance and displayed passively within search results. They are not interactive, nor do they introduce additional security risks associated with live, generative systems. Their purpose is to provide quick context, helping users evaluate relevance before opening an article.
Security and Privacy Safeguards
Our infrastructure adheres to rigorous security standards:
- End-to-end encryption protects institutional data across HeinOnline.
- Role-based access controls ensure only authorized staff have access to internal systems.
- No external reuse of private data. Summaries are generated only from HeinOnline’s licensed and preserved content.
Built on Librarianship Principles
We anchor every AI initiative in librarian values: transparency, privacy, preservation, and citation integrity. AI Summaries are designed to enhance discoverability, not replace primary sources, ensuring that research remains rooted in authoritative materials.