BUILT ON AIDEN OS

Everything
behind the agents

Aiden OS is the layer that decides what an agent may do, what it may spend, who it acts as, and what it leaves on the record. Skills and workflows run on it. Policy, identity and evidence bound it.

Skills & Workflows

The reusable units an agent runs. Author once, version them, and every agent in every play calls the same tested step.

Policy as Code

What each agent may touch, in which environment, at which autonomy rung — declared in version control, not configured in a console.

Guardrails & Approvals

Scope every agent by service, environment and change class, and put a named human on the changes you decide need one.

Identity & Access

Every agent holds its own scoped credential and shows up in your logs as itself. No shared key, no borrowed human account.

Tokenomics

A cost ceiling per run, per agent and per team, enforced before the spend — so autonomy never turns into an unbounded invoice.

Audit & Evidence

Every decision, the objective version behind it and both agents’ positions, written to a signed record you can hand an auditor.

Integrations

Your pipeline, ticketing and monitoring stay the system of execution. Agents act through them; the world model reads from them.

Model Routing

Every step goes to the model that suits it, balanced across quality, speed and cost, without anyone hard-coding a model into a workflow.

Bounded by policy.
Running on the tools you already have.

|Aiden world model|

Grounded in how you actually run production

The world model ingests data across your stack all the way from infrastructure to code to production, and your tribal knowledge. All Aiden agents operate with this shared context.

// What we capture

    Drag to explore

    // Who draws on it

      Context graph

      World Model provides the operational context needed to operate autonomously

      Policy and rules

      Approvals, blast-radius limits, and org standards so agents act inside the same gates humans already trust.

      Operational memory

      Every result updates future gates and runbooks for the next agent run.

      GOVERNED AUTONOMY

      Humans keep authority.
      The factory absorbs toil.

      You define goals, guardrails and autonomy levels. Aiden gathers evidence, makes decisions, and executes with continuous learning

      Where it runs

      Sources of truth across code with infra, runtime state, and knowledge, queryable in real time.

      What it may do

      Governance with RBAC and policy bound every agent the same way they bound humans. Human-in-the-loop when the stakes require it.

      What it actually did

      Decision traces for each input, each decision, and each action. Every trace is durable and replayable for audit.

      Set autonomy per task, per environment, and per team
      Human in the loop
      Autonomous
      Deterministic
      faq

      Frequently Asked Questions

      What is an Autonomous Operations Platform?
      How is this different from AIOps or observability tools?
      What does "autonomous" actually mean — do agents take action without human approval?
      We already have Terraform, Kubernetes, and a monitoring stack. How does StackGen fit in?
      How do teams typically get started?

      See the factory live.

      Book Demo