Automato AI Sales
Give visual form to campaigns and service workflows.
Components and charts belong to a UI prototype. Dashboard values are static demonstration data, not real sales or AI metrics.
Prototype objective
Automato AI Sales is a UI prototype for a campaigns-and-service SaaS product. It explores landing, registration, login and dashboard with a consistent visual language.
Its scope is frontend: there is no evidence of an AI engine integrated into this dashboard. It differs from IA Vendedora, whose repository contains channel and model integrations.
Composition and navigation
React and TypeScript organize pages and components; Vite supports development builds. React Router represents navigation between public surfaces and dashboard.
Sidebar, header, metric cards, campaign lists and recent activity split presentation responsibilities. Reuse reduces duplicated visual structure across screens.
Dashboard and charts
The dashboard combines cards and a Recharts area chart. Data and indicators are frontend-defined, making the prototype navigable without an API. Responsive layout organizes cards and charts for available space.
Displayed values are demonstration data, not production business metrics. Real integration needs query contracts, loading and error states and consistent indicator definitions.
Forms and interaction states
useState-controlled fields organize email, password and loading state. Login simulates a delay, displays a toast and navigates to the dashboard.
This simulation is a prototyping choice, not authentication. A real version must replace the timeout with server verification, sessions and route protection.
Visual system and maintenance
Tailwind CSS and UI components define spacing, colors, forms and states. Icons and typographic hierarchy distinguish navigation, figures and actions while cards share reusable structure.
Presentation architecture demonstrates component composition, rather than treating installed dependencies as automatically used features. Accessibility needs keyboard and screen-reader verification beyond appearance.
Learning and evolution
The project demonstrates product UI, routing, forms, states and demonstration-data visualization. Review inspected the frontend without measuring conversion or attributing sales outcomes to the prototype.
Next steps include API contracts, real authentication, failure states, component tests and E2E scenarios. The visual foundation can evolve while preserving the distinction between demo and connected product.
Private repositories. Authorized summaries; source code is not distributed here.