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Kodosumi

Open-source runtime for deploying and scaling AI agents.

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

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

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