Ship 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 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.shOpen the console. Create an org. Deploy your first agent.
Stop clicking. Version your agent infrastructure.
resource "agyn_agent" "data_engineer" {
name = "data-engineer"
model = "claude-sonnet-4-6"
sandbox_image = "agyn/sandbox:latest"
idle_timeout = "10m"
mcp = ["filesystem", "postgres", "slack"]
}
resource "agyn_agent" "support" {
name = "support-agent"
model = "gpt-4o"
sandbox_image = "agyn/sandbox:latest"
idle_timeout = "2m"
mcp = ["zendesk", "notion"]
}terraform init && terraform applyEach agent is a first-class citizen:
- Isolated sandbox — own container, filesystem, env vars, secrets
- MCPs in separate containers — full process isolation per tool
- Observability built in — token usage, compute, activity logs
- Auto-scaling — agents spin up on demand, terminate on idle
AGPL-3.0