Exposes course documents as searchable resources and provides tools for reading, study task management, and source-grounded quiz prompts. Supports hybrid retrieval and integration with DeepSeek-based agents.
Ingest, query, and generate study materials from documents (PDF, DOCX, Markdown, images, web pages) using vector search, knowledge graph, and study tools through OpenCode chat.
Enables AI assistants to interact with local documents (PDF, Markdown, TXT) through tools for discovery, reading, extraction, summarization, comparison, keyword extraction, search, and analysis, ensuring privacy and offline capability.
Enables personalized AI tutoring by allowing students to upload PDF/DOCX study materials that are processed and indexed for semantic search. Provides intelligent responses based on the student's own learning materials using RAG technology.
Converts study materials like PDFs, slides, and DOCX into a searchable vector database with semantic search, summarization, and flashcard generation, integrated with Notion.
Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.