Develop reported problems into reviewable changes
Let a coding agent prepare an isolated worktree, then review the diff and evidence before anything applies.
OPENORBIT · LOCAL CONTROL PLANE
Turn AI product work into reviewable improvement.
Personas find work. Coding agents prepare isolated changes. Your team reviews evidence and decides what applies.
View on GitHub
START WITH A WORKING LOOP
From a guided quick start to retained operational history.
Connect runners, test cases, environments, policy and model profiles. Every run keeps the evidence needed for the next decision.
What you can do with OpenOrbit
Use the coding agent your team already trusts
Connect your preferred AI coding agent instead of being tied to one provider.
Give AI personas meaningful product work
Explore from a defined point of view, report problems, and retain the evidence behind them.
Improve AI systems over time
Keep runs, feedback, proposals, and decisions as operational history.
Reuse the assets that make a run repeatable
Manage personas, prompts, model profiles, test cases, environments, and workflows.
Operate through Assistant, MCP, and OpenAPI
Ask about the screen in front of you and connect your own tools to the same local data.
RETAINED EVIDENCE
Inspect what happened behind every run.
Review lifecycle progress, logs, metrics and supervisor feedback in one control room.
HUMAN APPROVAL
Review AI-created changes before they apply.
Inspect rationale, acceptance evidence and isolated Git worktree diffs. AI prepares work; people decide.
Run locally in minutes.
python -m pip install openorbit
orbit run