See How Your Service Really Runs.
Design How It Could Run Better.

Three things, as one connected model: who does the work and who it's for (roles, teams, customers, personas — every actor is a segment, told apart by its type), what needs doing (the stable jobs, and the competing solutions currently hired for them), and what the work runs on (every tool, system, document, and piece of equipment, staged under the exact step that uses it). It's process mining for human work — instead of reading system logs, you capture how people really operate from documents, interviews, and observation.

A diagram is a picture of what somebody drew. RoleDream is a model you can query. Draw the same system in five Miro boards and you have five disconnected shapes that nothing keeps in sync. In RoleDream it's one resource, linked to every job that touches it — so "what breaks if we replace this?" has an answer, and the answer stays right as the map changes. Those are the questions a board can't answer.

Those suites also model processes rigorously — but they're built as enterprise rollouts: consultant-led implementations, modeling notation to learn, enterprise pricing. RoleDream sits in the gap between them and the whiteboard tools: a queryable who/what/how model you get self-serve. Sign up, hand your AI assistant an interview or a process document, and have your first map the same day — no notation, no rollout project.

No. JTBD is one of the three traditions the model unifies, alongside Service Design and plain process mapping. If you just want to document how a process runs and what it depends on, the same objects and links carry that perfectly well — you can use the framings or ignore them entirely.

Jobs are stable goals — "deliver order" doesn't change. Solutions are the concrete ways to do them, and they compete: "deliver by car" against "deliver by drone", each with its own steps, resources, and trade-offs. You don't hire a job; you hire a solution for it, and you fire it when something better comes along. Hiring decisions record every switch and the reason behind it, so the map builds a history of what actually works.

Under every step, resources stage into two lanes: Frontstage above the line of visibility — what the customer can see, like an app screen or a service counter — and Backstage below it, the systems and tools working behind the scenes. It's the classic service-blueprint line of visibility, drawn natively on the canvas instead of annotated on top of a diagram.

RoleDream runs a hosted MCP server, so it connects to any AI assistant or CLI that speaks the Model Context Protocol — you keep whichever one your team already uses. Setup is a one-time OAuth authorization. What makes it work isn't the connection but the briefing: the assistant is taught the model itself, so it separates real jobs from tool complaints, keeps individual roles apart from groups, and stages resources under the right steps. Paste an interview transcript or a process document into the chat and you get a draft to review, not a pile of objects.

That's the normal case, and it's the point. Most source material is messy — activities, complaints about tools, half-remembered process. You don't need to clean it up first: hand over what you have, and the assistant drafts a mapping for you to correct. Expect a handful of real jobs per role with plenty of steps and evidence underneath them. Start with one role or one flow, get it right, and grow from there.

Yes. Those regulations ask you to map critical functions to the roles, systems, and third parties that keep them running — and that chain is exactly what the model holds: jobs broken into steps, each step staged with the resources it depends on and the roles responsible. Because it's a queryable model rather than a drawing, the mapping stays current as operations change, and "which functions does this system support?" always has an answer you can export for an audit.

Yes. Your data is encrypted in transit and at rest. RoleDream maintains SOC 2 readiness and ISO 27001 alignment with continuous real-time monitoring. We follow GDPR-compliant data handling practices. View our Security Audit Report for details.