Showing 1 open source project for "world monitor"

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  • Employees get more done with Rippling Icon
    Employees get more done with Rippling

    Streamline your business with an all-in-one platform for HR, IT, payroll, and spend management.

    Effortlessly manage the entire employee lifecycle, from hiring to benefits administration. Automate HR tasks, ensure compliance, and streamline approvals. Simplify IT with device management, software access, and compliance monitoring, all from one dashboard. Enjoy timely payroll, real-time financial visibility, and dynamic spend policies. Rippling empowers your business to save time, reduce costs, and enhance efficiency, allowing you to focus on growth. Experience the power of unified management with Rippling today.
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  • Remote Network Monitoring and Management for an IoT World Icon
    Remote Network Monitoring and Management for an IoT World

    The Only RMM Solution You Need

    Domotz is the premier Remote Network Monitoring and Management platform for IoT. We offer powerful network management software for MSP's, Integrators, Security Professionals, and Business Owners. Domotz enables the complete solution to cost-effectively manage and monitor your customers’ networks with plug and play setup, a friendly UX, and a comprehensive feature set, accessible from any desktop browser or mobile device. Utilize one interface to manage multiple networks at multiple locations anywhere in the World. One person can deploy remote monitoring and management in less than 15 minutes.
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    Arize Phoenix

    Arize Phoenix

    Uncover insights, surface problems, monitor, and fine tune your LLM

    ...Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting.
    Downloads: 13 This Week
    Last Update:
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