by agynio
Agyn is an open-source Kubernetes-native runtime that moves AI agents from laptops to company infrastructure with the controls enterprises need.
# Add to your Claude Code skills
git clone https://github.com/agynio/platformShip AI agents to your company. Safely.

You built the agent. Now how do you let the rest of the company use it — without exposing secrets, blowing budgets, or losing control? Agyn is an open-source, Kubernetes-native platform that moves agents from laptops to company infrastructure with the controls enterprises need.
| Problem | Agyn | |---------|------| | Agents run on individual laptops | Centralized deployment on your infrastructure | | Secrets passed directly to models | Secrets isolated, never exposed to the model | | No budget visibility or limits | Spend caps at any level — per agent, per team, per org | | No access control | RBAC, SSO, audit logs | | Locked to one vendor | Agent-agnostic, model-agnostic | | Can't scale | Horizontal scaling, auto-termination on idle |
git clone https://github.com/agynio/bootstrap.git
cd bootstrap
./apply.sh
Open the console. Create an org. Deploy your first agent.
Want a ready-made fleet to play with? Apply agynio/demo-agent — a Terraform config that provisions a support, marketing, and data-engineer agent in one command.
For production installs, see Self-host install.
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Stop clicking. Version your agent infrastructure.
resource "agyn_agent" "support" {
organization_id = agyn_organization.acme.id
name = "Support"
nickname = "support"
model = agyn_llm_model.gpt_4o.name
image = "ghcr.io/agynio/agent-runtime:v1.0.0"
init_image = "ghcr.io/agynio/agent-init-codex:v1.0.0"
idle_timeout = "5m"
availability = "internal"
}
resource "agyn_agent_mcp" "zendesk" {
agent_id = agyn_agent.support.id
name = "zendesk"
image = "ghcr.io/acme/zendesk-mcp:latest"
envs = [
{
name = "ZENDESK_TOKEN"
secret_id = agyn_secret.zendesk_token.id
},
]
}
terraform init && terraform apply
See the Terraform provider reference for every resource.
Each agent is a first-class citizen:
Full architecture: docs/operate/architecture.md.
| Video | What it shows | |---|---| | | Agyn in 5 minutes — From clean cluster to a working agent answering a chat message. End-to-end tour. | | Coming soon | Deploying agents with Terraform — Define an agent fleet as code, apply it, talk to them. | | Coming soon | Inspecting a run with Tracing — Every LLM call, every tool execution, every context decision. |
Full docs live in docs/:
Agyn is split across focused repositories. The most useful starting points:
| Repo | What it is |
|---|---|
| agynio/platform | This repo. Documentation hub. |
| agynio/architecture | Source-of-truth architecture and product specs. |
| agynio/bootstrap | One-command local install (k3d + Terraform). |
| agynio/platform-charts | Production Helm charts. |
| agynio/api | Protobuf schemas for every service. |
| agynio/terraform-provider-agyn | Terraform provider. |
| agynio/agyn-cli | Platform CLI. |
| agynio/console-app · chat-app · tracing-app | Browser UIs. |
| agynio/agent-init-codex · agent-init-claude · agent-init-agn | Agent CLI init images. |
Full list with descriptions: docs/reference/service-catalog.md.
Good places to start:
AGPL-3.0