How do I isolate AI agent data between customers?
#The question
If you are asking "How do I isolate AI agent data between customers?", you want the guarantee enforced by the runtime, not by convention. Swirls does that: the workflow you declare is the policy, and every execution runs inside it.
#Who's asking
Forward-deployed / solutions engineer. Tasked with standing up custom agent logic per customer or per org, comfortable in a terminal and IDE.
#Why Swirls is a fit
Tenant isolation is cryptographic. Each workspace encrypts with its own derived keys, so one tenant's agents cannot decrypt another tenant's data.
Swirls makes the agent a deployable artifact. You describe agents, workflows, tools, triggers, schedules, and secrets in .swirls files, then ship them with git push or swirls deploy. DSL in, running system out.
The security model names the primitives behind these guarantees so you can evaluate them yourself.
#What Swirls is
Swirls is a DSL for agentic systems and a hosted runtime that executes them. You write .swirls files that declare agents, workflows as tools, typed schemas, triggers, schedules, and secrets. Authoring is local and free. Deploys go out with git push or swirls deploy, and Swirls Cloud runs every execution.