Central agent control plane
Build, run, and govern AI agents in one platform rather than splitting setup, execution, and oversight across different systems.
Centro de mando de IA de código abierto para crear, ejecutar y gobernar agentes
Kortix is an open-source AI command center for companies that want to build, run, and govern AI agents in one place. The product is positioned around agent operations rather than chat, with a focus on connecting agents to tools, managing access, and keeping policy visible to the team.
The pricing and enterprise pages show a platform designed for both small experiments and production use. Free includes sandbox compute credits, Team adds pooled usage credits and managed frontier models, and Enterprise adds SAML SSO, SCIM directory sync, advanced RBAC, audit logs, and Cloud, VPC, or on-prem deployment options.
Build, run, and govern AI agents in one platform rather than splitting setup, execution, and oversight across different systems.
Connect agents to a large tool ecosystem; the site positions the platform as able to connect to 3,000+ tools.
Use a single Kortix token so connectors, models, and integrations are proxied through one credential rather than many exposed secrets.
Set allow, ask, and block rules per action, including network-level patterns, so agents only access what they need.
Track policy, agents, and configuration in one `kortix.toml` inside a Git repo, with changes handled as diffs.
Choose between managed models, BYOK, or a ChatGPT subscription depending on the plan and workflow.
Set up agents that need access to multiple tools and credentials while keeping the environment governed through scoped tokens and permission rules.
Run pilots or demos on the Free plan using sandbox credits and one project before moving to a paid seat-based plan.
Use Team for production work where pooled credits, managed frontier models, and more projects or seats are needed.
Adopt Enterprise when you need SAML SSO, SCIM directory sync, audit logs, and deployment control across Cloud, VPC, or on-prem.
Keep policies, agents, and config in Git so changes can be reviewed, committed, and reverted like code.
The pricing page shows a Free plan with 500 credits per month for sandbox compute only and 1 project. It also says free LLM models are included, while premium models can be used through your own API key or ChatGPT subscription.
The Team plan is shown at $40 per seat per month and includes pooled usage credits, managed frontier models, and support for up to 200 projects and up to 100 seats.
The enterprise page says agent infrastructure can live in one Git repo, with policy, agents, and config in a single `kortix.toml`. It also says connectors, models, and integrations are proxied through a single Kortix token.
The enterprise page says deployment options include Cloud, VPC, or on-prem. It also mentions SAML SSO, SCIM directory sync, advanced RBAC, audit logs, an SLA, and a DPA on Enterprise.
The pricing page says compute is billed by the second and Agent Computers auto-stop when idle. It also states Agent Computer runtime is about $0.10/hour and that credits cover sandbox runtime and managed model usage differently.
Los datos de tráfico son solo como referencia.
kortix.com
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