Showing 2 open source projects for "self-learning ai"

View related business solutions
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
    Try for free
  • 1
    Ainee

    Ainee

    Ainee - AI Notetaking and Learning Companion

    ...Enhance your learning with our AI voice recorder, article summarizer AI, and AI quiz generator. Additionally, share your knowledge base with others to foster the flow of information and help new users benefit from collective insights. Experience smarter learning with Ainee today! How It Works - Effortless Knowledge Capture Across Formats - Enhance learning experience with AI-Driven Tools - Transform Study Materials into Dynamic Learning Formats - Share Insights and Knowledge Effortlessly
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    CIApp

    CIApp

    CIApp is an innovative application designed to track and count reps

    Automatic Repetition Counting: Detects and counts exercise repetitions (e.g., pull-ups, push-ups, squats) in real-time using AI-powered motion tracking. Reduces the need for manual counting, allowing users to focus fully on their workout. Advanced Computer Vision: Utilizes cutting-edge machine learning models to recognize movements and distinguish between exercise types. Works with both webcams and video uploads for ultimate flexibility. User-Friendly Interface: Simple and intuitive design for users of all fitness levels. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next