LiquidText
The infinite workspace for deep document analysis and multi-source synthesis.
The world's leading open-standard collaborative annotation layer for the web and digital documents.
Hypothesis is a mission-driven, open-source platform that enables a conversation layer over the entire web. Built on the W3C Web Annotation standard, it allows users to highlight and comment on any webpage, PDF, or EPUB without modifying the underlying source code. In the 2026 landscape, Hypothesis has solidified its position as the critical infrastructure for 'Human-in-the-Loop' AI training and verifiable digital provenance. Its technical architecture utilizes a decentralized approach, allowing for public, private, and institutional groups to collaborate securely. The platform integrates deeply with Learning Management Systems (LMS) via LTI standards, making it the industry standard for collaborative reading in higher education. By treating annotations as first-class digital citizens, Hypothesis provides a structured data stream (via its REST API) that researchers and developers use to map discourse, verify claims, and build collective intelligence databases. It functions as a browser-neutral extension or a script-injected overlay, ensuring high availability across all modern web environments while maintaining strict adherence to user privacy and data portability standards.
Supports LTI 1.3 standards for seamless, secure integration with major LMS platforms without requiring student account creation.
The infinite workspace for deep document analysis and multi-source synthesis.
Empower your teams to learn, practice, and perform with AI-driven sales enablement and microlearning.
Transform fragmented datasets into navigable, high-fidelity neural knowledge graphs for RAG orchestration.
The minimalist's gateway to focused reading and intelligent content archival.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Utilizes a modified PDF.js viewer to ensure annotations are mapped correctly even if the file name changes, using document fingerprints.
Advanced algorithms that re-attach annotations to text even if the underlying HTML structure or content slightly shifts.
Full support for Markdown formatting and LaTeX mathematical notation within the annotation body.
Comprehensive REST API allowing for full CRUD operations and filtered search of the global annotation database.
Generates unique URLs that automatically scroll the recipient to the exact highlighted section of a document.
The entire back-end (h) and front-end (client) are open-source, allowing for custom self-hosted instances.
Traditional peer review is siloed and disconnected from the text.
Registry Updated:2/7/2026
Final version is updated based on synchronized feedback.
Readers cannot see the verification process of an article in real-time.
Instructors can't track if students are actually reading assigned materials.