Kodosumi

Kodosumi

Open-source runtime for deploying and scaling AI agents.
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Kodosumi is an open-source runtime environment designed for developers to deploy and scale AI agents efficiently. It supports fast, scalable, and free deployment of agentic services, leveraging Ray for distributed computing. Ideal for enterprise-scale applications, it offers minimal configuration overhead and framework agnosticism.

Free
Kodosumi screen shot

How to use Kodosumi?

Kodosumi allows developers to deploy AI agents at scale with minimal setup. By using a single YAML config file, users can deploy agents locally or in the cloud, manage long-running workflows, and integrate with any LLMs or frameworks. It's built on Ray, ensuring reliability and scalability for complex agentic workflows.

Kodosumi 's Core Features

  • Framework agnostic, supporting any AI agent framework
  • Minimal configuration with a single YAML file
  • Built on Ray for scalable and reliable execution
  • Open-source with no vendor lock-in
  • Real-time monitoring and observability
  • Supports long-running and bursty agent workloads
  • Easy integration with existing AI models and tools

    • Kodosumi 's Use Cases

  • Developers looking to deploy scalable AI agents without vendor lock-in
  • Enterprises needing to manage complex, long-running AI workflows
  • Teams requiring real-time observability and debugging for AI services
  • Startups wanting to integrate open-source tools and LLMs flexibly
  • Researchers focusing on agentic workflows and distributed AI systems

    • Kodosumi 's FAQ

    Most impacted jobs

    Software Developers
    AI Researchers
    Data Scientists
    DevOps Engineers
    Machine Learning Engineers
    Technical Leads
    Startup Founders
    Enterprise Architects
    Cloud Engineers
    System Administrators

    Kodosumi 's Tags

    #AI Agents#Open Source#Scalability#Ray#Framework Agnostic#Real-time Monitoring#Distributed Computing

    Kodosumi 's Alternatives