What is ai agent runtime?
An AI agent runtime is the place a team of agents lives and runs in production. It gives agents tools to act, schedules to fire on, memory that survives restarts, approval gates for risky steps, and an audit trail of what happened. A chat that drafts a reply is a demo; a runtime is what keeps the work going at 3am.
What it isn't
Honest boundaries
Defining a category means saying what it is not — so adjacent tools aren't conflated.
- Not a single chatbot — the unit is a team of agents with roles, tools, and memory.
- Not a framework you assemble and operate — a runtime is hosted and always-on.
- Not serverless functions — agents are persistent and stateful, not triggered-and-forgotten.
From
Agents as local scripts, single chatbots, or serverless functions you babysit — demos that die when the laptop closes.
To
Persistent, stateful agent teams that run around the clock in isolated environments — observable, approvable, and auditable.
What to look for
A buyer's checklist
The questions that separate a runtime built for production from a tool built for demos.
Hosted & always-on
Does it run 24/7 as a managed service? If keeping it available is your job, it is a framework, not a runtime.
Persistent agents with memory
Do agents keep their identity, role, and context across runs — or are they re-instantiated each time?
Workflows you can inspect
Is the operating model real code you can read and version, or an opaque prompt that changes every run?
Oversight out of the box
Are approvals, an audit trail, and a dashboard built in — or do you wire them up yourself?
Where OrgSDK fits
OrgSDK is a hosted agent runtime. Persistent teams, versioned TypeScript workflows, schedules, durable memory and state, approvals, and a real-time dashboard are all built in. See the runtime page for the operational jobs a runtime owns.
See the product