Active Recall AI is a cutting-edge tool designed to improve students' learning experiences by utilizing artificial intelligence. It generates quizzes and writing tasks from uploaded study materials, helping users to understand and remember content better. By incorporating active recall and spaced repetition techniques, the tool aims to maximize study efficiency and ensure long-term retention of information. Whether you're preparing for exams or certifications, Active Recall AI provides a personalized learning experience tailored to your needs.

CertGenAI is an innovative AI-driven platform designed to generate customized practice tests for certification exams. It aims to provide an accessible and cost-effective way for professionals and students to enhance their skills and knowledge, preparing them thoroughly for various certification exams across different industries. By leveraging artificial intelligence, CertGenAI creates practice tests that adapt to user needs, ensuring comprehensive preparation.

ExamCram is a revolutionary app that uses artificial intelligence to transform the traditional study process. It converts lectures, notes, and various study materials into engaging and dynamic quizzes. Designed to make studying more efficient and effective, ExamCram caters to individual learning needs and helps solidify knowledge in a fun, interactive manner. Its quick quizzes and personalized approach make it an indispensable tool for students aiming to optimize their study sessions.

Mock Exam AI is a cutting-edge platform that leverages the power of Artificial Intelligence to help users create customized mock exams with ease. Users can manually add questions, generate new ones, and even include references in the form of links and PDFs. Premium users have no limit on question generation and can make their exams private. It’s an ideal tool for anyone preparing for upcoming exams who wants a streamlined and flexible testing experience.

SeeAct is designed to empower vision-language agents with a two-stage pipeline: a planning module powered by large language models generates subgoals based on observed scenes, and an execution module translates subgoals into environment-specific actions. A perception backbone extracts object and scene features from images or simulations. The modular architecture allows easy replacement of planners or perception networks and supports evaluation on AI2-THOR, Habitat, and custom environments. SeeAct accelerates research on interactive embodied AI by providing end-to-end task decomposition, grounding, and execution.