Empowering the global research community through open-access scientific publishing and a proprietary XML-first workflow.
Hindawi, now a fully integrated subsidiary of John Wiley & Sons, represents a cornerstone in the transition toward Open Science and digital-first scholarly communication. Its technical architecture is built around the 'Phenom' publishing system—a modern, end-to-end platform designed to manage the entire lifecycle of a manuscript from submission and peer review to production and dissemination. In 2026, Hindawi's market position is defined by its massive scale in the Gold Open Access sector, leveraging a decentralized editorial model that empowers global academic communities. Technically, the platform utilizes an XML-first production workflow, ensuring that research outputs are instantly machine-readable and highly discoverable via automated indexing across Scopus, Web of Science, and PubMed. Following its acquisition by Wiley, Hindawi has undergone significant quality control overhauls, integrating advanced AI-driven integrity checks to detect paper mill patterns and citation manipulation. The platform's 2026 strategy focuses on 'Research Integrity at Scale,' using automated forensic tools to validate data sets and image authenticity, making it a critical hub for researchers requiring rapid, validated, and open-access publication within the physical sciences, medicine, and engineering disciplines.
A proprietary cloud-native platform that automates the peer-review workflow and XML conversion process.
Accelerating scientific discovery through AI-enhanced open access publishing and peer-review automation.
The pioneer in open, post-publication peer review and transparent scholarly publishing.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Integrated tools to detect AI-generated text, image manipulation, and paper mill patterns during the submission phase.
Content is stored in JATS XML format from the start of production rather than post-PDF conversion.
A database of over 100,000 verified academics categorized by expertise using NLP-based matching.
Supports the Open Archives Initiative Protocol for Metadata Harvesting for seamless library integration.
Automatic recognition of author affiliation to trigger pre-negotiated institutional discounts.
Ensures all supplementary data is assigned its own DOI and archived in perpetuity.
Traditional journals take 12+ months to publish, which is too slow during a public health crisis.
Registry Updated:2/7/2026
Researchers funded by specific grants must publish in compliant open-access journals.
Data scientists need structured data from thousands of papers for AI training.