Deploy agentic services quickly with minimal configuration overhead
Users can define dependencies, environment variables, and deploy agents in seconds using a single YAML configuration file, reducing setup complexity and enabling rapid iteration
Kodosumi
Kodosumi
Runtime environment to execute agentic services at scale
Overview
What it is
Deploy and scale your AI agents with Kodosumi, the open-source runtime built for developers. Fast, scalable, and fully free to use.
Intent
I need it when
Orchestrate complex multi-agent systems with coordinated workflows
Kodosumi's Flow concept enables users to define automated processes where multiple agents coordinate and pass data between steps, allowing complex objectives to be accomplished through interconnected agent tasks
Build flexible AI agent workflows without vendor lock-in
Kodosumi is open source and framework-agnostic, supporting CrewAI, LangChain, FastAPI, and any Python framework, allowing users to use their preferred AI tools and maintain portability across platforms
Deploy and scale AI agents across multiple nodes in production environments
Kodosumi provides a distributed runtime built on Ray that enables seamless scaling from 1 node to 1,000+ nodes, allowing users to run agentic services reliably at enterprise scale with minimal configuration via a single YAML file
Monitor and observe AI agent operations in real-time
Built-in observability through the Ray dashboard gives full visibility into agent operations, resource usage (CPU, GPU), and pipeline execution status, enabling users to track agent performance and troubleshoot issues
Drop
Not a fit when
- User needs a fully managed SaaS platform without infrastructure setup or Ray cluster management
- User requires commercial support contracts or SLAs beyond community Discord support
- User lacks Python expertise or prefers no-code/low-code agent deployment
- User needs pre-built agent templates for specific industries without custom development
- User operates in environments where open-source software is prohibited or restricted
Commercials
Pricing
Open source with free installation via pip