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Beta

Flow is in beta. We are actively shaping the product, so things may change as we iterate. Your feedback is welcome.

Flow Overview

Flow is Mia-Platform's AI-driven development web application. You open it in the browser, describe what you want to build in natural language, and the assistant generates the code, runs it live in a sandboxed preview, and deploys it to a Mia-Platform project when you are ready.

Flow brings together three things developers normally juggle separately:

  • A chat-first interface for talking to an AI assistant that understands your project and the systems you have connected.
  • A live preview of the generated code, updated as you iterate with the assistant.
  • A catalog of reusable AI building blocks (agents, skills, prompts, specs, playbooks) that pre-configure the assistant for specific tasks, teams, or domains.

What you can do with Flow

  • Generate full-stack applications from a prompt. Frontend, backend, database schema, authentication, tests, and documentation are produced from a single natural-language description and iterated through follow-up messages.
  • Preview the result instantly. Each generation is rendered in a live preview inside the Canvas, so you can interact with the application as it grows.
  • Reach external systems through MCP. The assistant can call tools exposed by GitHub, GitLab, Azure DevOps, Atlassian, Grafana, Google Drive, Mia-Platform itself, and any custom MCP server you register.
  • Deploy to Mia-Platform. A connected Mia-Platform project becomes the target for the generated code: pushing from Flow triggers the project's CI/CD pipeline.

The main areas of the application

AreaWhat it is for
HomeQuick-start omnibar and recent conversations.
ChatConversational interface with the AI assistant.
CanvasCode editor and live preview for the project tied to a conversation.
AI FoundryManage reusable agents, skills, prompts, specs, and playbooks.
ConnectorsAuthenticate to the external systems Flow can act on.
MemoriesBrowse, rename, and reopen past conversations.
SettingsDefaults, advanced options, and preferences.

Where to go next

  • Getting started: sign in and open your first conversation.
  • Connected tools: understand how MCP integrations expose external systems to the AI.
  • Chat: the conversational interface and how sessions are persisted.
  • Code: the Canvas, live preview, and supported frameworks.
  • Agentic AI: agents, skills, playbooks, and how the assistant reasons.