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An AI-powered learning platform that turns sources into concept maps, flashcards, quizzes and summaries with multi-model chat.
AI cloud offering model APIs, GPU instances, and serverless GPUs; high traffic.
TypeScript backend-as-a-service with a reactive database, server functions, auth and file storage for full-stack and AI apps.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
No public pricing
No public pricing
- ✦Concept map builder
- ✦Flashcards with spaced repetition
- ✦AI quiz and summary generation
- ✦Import from PDFs, YouTube, websites, PubMed and arXiv
- ✦Multi-model AI chat (GPT, Claude, Gemini, Qwen)
- ✦Cross-format conversion and sharing
- ✦Model APIs
- ✦GPU Instances
- ✦Serverless GPUs
- ✦Custom Model Deployment
- ✦Reactive real-time database
- ✦TypeScript server functions (queries/mutations/actions)
- ✦Built-in authentication
- ✦Cron jobs and backend workflows
- ✦File storage, text and vector search
- ✦ACID transactions; open-source/self-host
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- →Visualizing and studying complex topics
- →Turning research sources into study materials
- →Literature review and dissertation prep
- →Deploy AI models for various applications using a simple API.
- →Scale AI applications with serverless GPUs.
- →Access high-performance GPUs for demanding workloads.
- →Deploy custom models with guaranteed performance and scalability.
- →Building real-time reactive apps
- →Backends for AI agents
- →Replacing Firebase or Supabase
- →Full-stack TypeScript development
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews