Diagramador de Flujos de Trabajo-AI workflow diagramming tool

Diagramador de Flujos de Trabajo — Purpose and Design

Diagramador de Flujos de Trabajo is a specialized assistant for producing professional workflow diagrams that conform to Bizagi-style standards and best-practice business process modeling. Its core design purpose is to translate business requirements and operational steps into clear, executable process diagrams that identify Pools (process boundaries), Lanes (task executors), Phases (time or stage-based groupings), tasks, gateways (decisions), events, and artifacts so the result can be used for analysis, automation handoff, compliance, and continuous improvement. Key functions include: (1) structuring processes into Pools and Lanes so responsibilities are explicit (the system enforces the guideline that Lanes represent the performing actor or role); (2) organizing work into Phases to reflect lifecycle stages, approvals, or time-based milestones; (3) producing tasks with precise descriptions, preconditions, inputs/outputs, and decision criteria; (4) ensuring notation and structure are Bizagi-friendly so models can be directly implemented or exported into Bizagi or similar BPM tools; and (5) generating delivery artifacts such as step-by-step swimlane diagrams, role task lists, RACI matrices, and implementation-ready documentation. Examples / scenarios: • Example 1 — New employee onboarding: Diagramador breaks onboarding into a Pool named "Onboarding ProcessJSON code correction", phases like "Pre-hire", "First Day", "First 30 Days"; Lanes for HR, IT, Hiring Manager; tasks such as "Create user account" (IT), "Complete orientation" (Hiring Manager). The output: a Bizagi-compatible swimlane diagram and a checklist that can be assigned in an HR system. • Example 2 — Invoice approval: Pool "Accounts Payable", phases "Receipt", "Validation", "Approval", Lane (Executant): Accounts Payable Clerk, Department Approver, Finance Controller. Tasks specify required documents, validation rules, SLA timers and escalation gateways. The model supports simulation to locate bottlenecks and produces an export for automation with an RPA bot or Bizagi-process implementation. Design emphasis: clarity of responsibilities (lanes), repeatable structure (phases), and practical handoff (exportable models, task-level detail, acceptance criteria).