Showing 2 open source projects for "framework python"

View related business solutions
  • SoftCo: Enterprise Invoice and P2P Automation Software Icon
    SoftCo: Enterprise Invoice and P2P Automation Software

    For companies that process over 20,000 invoices per year

    SoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
    Learn More
  • Premier Construction Software Icon
    Premier Construction Software

    Premier is a global leader in financial construction ERP software.

    Rated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
    Learn More
  • 1
    Archipelago

    Archipelago

    Archipelago Multi-Game Randomizer and Server

    Archipelago is an open-source multi-game randomizer framework that allows multiple players to play different games simultaneously while sharing a unified item randomization system. The software creates what is known as a “multiworld,” where items that normally appear in one game may instead appear in another player’s game. When a player finds an item belonging to someone else, the system automatically sends that item to the correct player through a networked server. This design encourages...
    Downloads: 18 This Week
    Last Update:
    See Project
  • 2
    DreamerV3

    DreamerV3

    Mastering Diverse Domains through World Models

    DreamerV3 is an open-source implementation of a reinforcement learning algorithm that uses world models to train intelligent agents capable of learning complex behaviors across many environments. The system works by building an internal model of the environment and then using that model to simulate possible future outcomes of actions, allowing the agent to learn from imagined experiences rather than only from real interactions. This approach enables the algorithm to efficiently learn...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB