The core engine analyzes scholarly article content in real-time using natural language processing to find and suggest the most semantically related articles from across its network.
Creates a federated ecosystem where thousands of academic journals and publishers participate, allowing traffic to flow between them based on content relevance.
Provides easy-to-install widgets (e.g., 'Trending Articles' or 'Recommended for You') that publishers can place on their article pages to display recommendations.
Offers publishers a dedicated dashboard to track key metrics such as recommendations served, clicks, referral traffic received and sent, and engagement rates.
Enables publishers to promote specific articles or journal issues to a highly targeted audience reading related content elsewhere in the network.
Academic publishers integrate TrendMD to surface their articles to researchers who are actively reading related work on other publisher sites. This places relevant content in front of a highly engaged audience at the perfect moment, increasing the likelihood of clicks, reads, and subsequent citations. This directly addresses the 'discoverability' challenge in a crowded publishing landscape.
Publishers use the network to participate in a structured traffic exchange. While their site sends readers to other relevant articles, they simultaneously receive qualified traffic from other publishers in the network. This creates a virtuous cycle that boosts overall site visits and pageviews without relying solely on search engines or direct marketing.
Journal website managers implement the recommendation widget to provide immediate value to readers. After finishing an article, researchers are presented with a curated list of 'next reads,' reducing their search effort and keeping them engaged on the publisher's platform or within the scholarly network longer, which improves key user experience metrics.
Learned societies or journals launching a special issue or highlighting a key paper can use TrendMD's targeting tools to ensure that promotion reaches readers who have demonstrated interest in that niche. This makes marketing budgets more efficient and helps important research gain traction more quickly.
Publishing directors and editors use the analytics dashboard to see which of their articles are most recommended and which external articles are drawing traffic away. This provides insights into trending research topics, competitor performance, and the relative appeal of different article types within their portfolio.
Sign in to leave a review
3D Slash is a unique, block-based 3D modeling software designed to make 3D design intuitive and accessible for everyone, from children and educators to hobbyists and professionals. Inspired by the visual simplicity of retro video games, it uses a 'destruction' and 'construction' metaphor where users carve models out of a virtual block of material using tools like a hammer, chisel, and trowel, rather than manipulating complex vertices and polygons. This gamified approach significantly lowers the learning curve associated with traditional CAD software. It is widely used in educational settings to teach STEM concepts, design thinking, and spatial reasoning. Users can create models for 3D printing, game assets, architectural visualizations, and simple prototypes directly in a web browser or via desktop applications. The platform emphasizes creativity, speed, and fun, positioning itself as a bridge between playful digital making and practical 3D output.
Achieve3000 is an adaptive literacy platform designed primarily for K-12 education, focusing on improving reading comprehension and critical thinking skills. It uses proprietary AI and natural language processing to dynamically adjust the reading level of nonfiction articles to match each student's individual Lexile measure, a standard for assessing reading ability. The platform provides differentiated instruction by delivering the same core content at multiple reading levels, allowing all students in a classroom to engage with grade-appropriate topics while reading at their own level. It is widely used in schools and districts across the United States to support English Language Arts instruction, intervention programs, and college and career readiness. The system includes embedded assessments, writing prompts, and data dashboards for teachers to monitor student progress. By providing personalized, leveled content, it aims to accelerate literacy growth, particularly for struggling readers and English language learners.
Acuant is an AI-powered legal research and document analysis platform designed to assist legal professionals, such as lawyers, paralegals, and corporate counsel, in navigating complex legal information. It leverages advanced natural language processing and machine learning to parse vast databases of case law, statutes, regulations, and legal precedents. The tool helps users quickly find relevant legal authorities, analyze documents for key clauses and risks, and prepare for litigation or transactions. By automating time-consuming research tasks, Acuant aims to improve accuracy, reduce manual effort, and enable legal teams to focus on higher-value strategic work. It is positioned as a modern solution for law firms and in-house legal departments seeking to enhance productivity and decision-making through AI.
