Learn how AgentOS and Kortix differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai agent platforms is best for you.
Last 30 days
Last commit
8 hours agoRepository age
1 yearVersion
v0.15.27License
Apache-2.0Repository
framersai/agentos
Last 30 days
Last commit
6 hours agoRepository age
2 yearsVersion
v0.14.8License
Elastic-2.0Self-hosted
YesRepository
kortix-ai/suna
Kortix appears to have several advantages over AgentOS, particularly in popularity, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Kortix significantly outpaces AgentOS in community adoption with 20,320 stars compared to 683 stars on GitHub. This 29.8x difference suggests Kortix has a much larger and more active community. In terms of developer contributions, Kortix has 3,439 forks, indicating strong developer engagement.
AgentOS is growing faster, adding 10 stars in the last 30 days (+1.5%) against adding 84 stars for Kortix (+0.4%). AgentOS is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with AgentOS last updated 8 hours ago and Kortix 6 hours ago.
Both tools share common technology foundations, being built with JavaScript, Typescript. However, they differ in their additional technology choices: Kortix leverages CSS, Bash, JSX, Python, Next.js.
Kortix has been in development longer, starting 2 years ago, compared to AgentOS which began 1 year ago. This 1.1-year head start suggests Kortix may have more mature features and established processes.
The projects use different licenses: AgentOS is licensed under Apache-2.0 while Kortix uses Elastic-2.0. Consider the licensing requirements when choosing for your project.
Both tools serve similar use cases in AI Agent Platforms.
Kortix provides self-hosting options for complete data control and customization, while AgentOS may be primarily cloud-based or require different deployment approaches.