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AI process mapping

AI process mapping, from a description to a governed design

Traditional process mapping is slow archaeology: workshops, sticky notes, and a diagram that is out of date before it is exported. AI process mapping flips the effort. You describe the process the way you would explain it to a colleague, and the map appears, structured, editable and ready to defend.

How mapping works here

The Agentic AI Process Designer gives you three doors into the same canvas. Describe: write the process in plain words; an intake gate asks a few targeted questions if key facts are missing, then the AI generates the full map. Draw: classic drag-and-drop with a 24-block palette. Interview: a discovery consultant asks short questions while the brief board fills in live, which is ideal for client workshops.

Every generated map is a real model, not a picture. Steps carry executors, systems, volumes and minutes per run. Decisions branch. Gates mark where humans approve. Data and applications appear as first-class blocks connected to the steps that touch them.

The map that answers "who should do this"

Where this tool departs from every classic mapper: the canvas is organised in lanes by executor: Humans, Hybrid, AI Agents, Systems, Data. The point of mapping a process in 2026 is not to document it; it is to decide, step by step, what stays human and what an AI agent can take over, with what supervision. The map and that decision are the same artifact. Read more about the redesign side in business process redesign with AI agents.

From map to numbers and delivery

Because the map is structured, everything downstream is one click away: a governance check across 11 rules, a business case in euros built from your volumes and live AI model prices, build-ready micro-task blueprints per step, and a delivery board with owners and due dates. See the whole flow on the home page, or compare with classic tools in process mapping software.

an as-is process map generated from a text description, with all steps in the humans lane
An as-is map generated from four sentences of description: claims handling at an insurance broker.

Frequently asked questions

What is AI process mapping?

AI process mapping uses artificial intelligence to turn a plain-language description of how work happens into a structured process map. Instead of dragging boxes for hours, you describe the process (or answer an interview) and the AI produces the map: steps, decisions, systems, data and handoffs, ready to refine.

Can AI really map a process from a text description?

Yes, if the description carries the essentials: who does what, in which systems, at what volumes, and where it hurts. When your description is thin, the designer asks two to four targeted questions before generating, which is what separates a usable map from a generic diagram.

How is this different from asking a chatbot to draw a flowchart?

A chatbot gives you a picture. A process design studio gives you a model: every step has an executor, an autonomy level, a risk profile and a cost. That structure is what lets the tool run governance checks, compute a business case and generate implementation blueprints from the same map.

What happens to the text I submit?

Your descriptions are processed by a commercial AI model under terms where API inputs and outputs are not used for model training by default, and your designs are stored in EU datacenters. The full details are in the privacy policy.

Map your first process from a description

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