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Build software with your own AI team.

Describe an idea. A Master Agent plans it, specialist agents design, code and test it, and the real app runs in a live preview while you watch.

The Jea Labs Studio workspace: a live preview of a generated Fitness Companion App with two saved workouts on the left, the AI team with each agent's real status on the right, and the Master Agent's chat messages at the bottom.
The workspace: the generated app runs on the left, the team reports real task states on the right.
How it works

From idea to a running, tested app

Every screenshot below is from the actual studio building a “Fitness Companion App”. No terminal, Git or setup needed.

1

Describe your idea

Plain language is enough: who it's for and what people should be able to do.

The new project form with a project name and a plain-language description of a workout logging app.
2

Review the plan before anything is built

The Master Agent writes requirements, testable acceptance criteria, the API design and a task plan with dependencies. Nothing starts until you approve it.

Plan review showing requirements, acceptance criteria, architecture endpoints and a six-task plan.
3

Watch the team work

Tasks run in dependency order. Agents that own different files work in parallel; the others wait. Each character's animation and status come from its real task state.

  • Every change is checkpointed before it's applied
  • Code that fails checks is rolled back and retried
Mid-build: the designer and database expert are being reviewed while the frontend, backend and QA agents wait for their dependencies.
4

Use the real app, live

The preview is the generated application running in a sandbox, not a mockup. Add data, switch between desktop, tablet and phone sizes, or open it full screen.

The live preview with two workouts saved and the weekly stats updated.
5

Ask for changes in chat

“Add a field called intensity.” The Master works out who's affected and only involves them. Here the database, backend and frontend agents updated their files, the designer stayed idle, and QA re-ran the tests. Data you entered is kept.

The Team tab after the change: the database, backend and frontend agents and QA completed their tasks while the designer stayed idle.
6

Inspect everything

Every agent output is versioned with a diff, every test run keeps its raw output, and any checkpoint can be restored.

A diff of an agent's output showing added and removed lines.
Your AI team

Specialists you can customize and reuse

Every studio starts with a Master Agent and five specialists. Add your own from templates or from scratch: name, character, role, instructions, task types, tools, owned files, model and limits. Each edit is versioned.

My AI Team page listing the Master Agent and specialist agents with their task types and owned files.

Matched by capability, not name

The Master assigns work by task type, tools, permissions and expertise.

No stepping on each other

Each agent owns specific files. Writes outside them are rejected.

Platform rules come first

Custom instructions can't override the security rules, which are also enforced in code.

UI/UX DesignerFrontend DeveloperBackend DeveloperDatabase ExpertQA Tester React Frontend ExpertLaravel Backend ExpertDatabase ArchitectAPI Integration SpecialistSecurity Reviewer SEO SpecialistDocumentation WriterMobile App DeveloperBusiness Requirements Analyst
Real, not mocked

Nothing on screen is faked

A rule the whole studio is built around.

Real preview

The app you see is the generated code running, served from its own isolated origin.

Real test results

QA runs actual tests and the studio stores the test runner's raw output. Failures go back to the agent that owns the code.

Real progress

Progress bars and character states come from saved tasks, not timers. Idle agents stay still.

Raw test runner output showing passing tests.
Raw output from the test runner, kept for every run.
The studio on a phone, showing the live preview at the top.
Works on a phone too.
Current status

Where the studio is today

Availability
In development and running locally. There is no public sign-up yet.
AI models
Claude support is built in. The screenshots on this page were made in offline mode, which uses a built-in template engine instead of an AI model: the code, preview and tests are real, but it handles a fixed set of app types and change requests.
Generated apps
Currently small web apps built on Node.js with no third-party packages, so they run without installing anything.
Deployment
One-click publishing isn't built yet. Projects can be exported as code.