Showing 3 open source projects for "database"

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
  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

    Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
    Explore Apify Store
  • 1
    SuperDuperDB

    SuperDuperDB

    Integrate, train and manage any AI models and APIs with your database

    Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. ...
    Downloads: 3 This Week
    Last Update:
    See Project
  • 2
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    ...This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.
    Downloads: 3 This Week
    Last Update:
    See Project
  • 3
    EvaDB

    EvaDB

    Database system for building simpler and faster AI-powered application

    Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
    Downloads: 4 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next