AI development
orchestration.
Describe a feature in plain English. Parton plans, parallelizes, and ships it — with tests, commits, and a PR.
"add invoice export"
Decomposes the feature into stories, assigns coordination domains, orders into waves
Create invoices table, add foreign keys to users
CSV serialization with configurable delimiters
PDF generation with company branding template
POST /invoices/:id/export endpoint
Export dialog with format picker and download
Integration tests for export flow end-to-end
6 commits · typecheck, lint, tests passed · branch ready for review
Install
One command. That's it.
Works on macOS and Linux.
AI coding today is powerful but chaotic.
Prompt chaos
Every request starts from scratch. You re-explain context, re-describe architecture, and hope the AI remembers what you said three prompts ago.
Context overload
Large codebases exceed context windows. The AI sees fragments, misses dependencies, and produces changes that break things it never knew existed.
No coordination
Multiple AI sessions edit the same files with no awareness of each other. Merge conflicts, duplicated work, and silent regressions pile up.
AI with the right context.
Most AI tools send your entire repository to the model — or rely on approximate search. Parton analyzes the repo graph first and builds a targeted context for every task.
Waves & Lanes.
Waves run one after another. Lanes within a wave run side by side.
Parton understands your repository.
Before executing any changes, Parton indexes your codebase structure, dependencies, and patterns — so every AI worker operates with full context.
Dependency graph analysis
Parton builds a full dependency graph of your codebase — modules, imports, exports — so the planner knows which files depend on which.
Touch set prediction
Before execution, each lane declares its predicted file touch set. The scheduler uses this to detect conflicts and prevent parallel edits to the same files.
Dependency cone analysis
For any given change, Parton computes the dependency cone — all files that could be affected — ensuring AI workers receive the right context.
Safe parallel execution.
The scheduler detects conflicts, coordinates AI work, and automatically serializes risky operations — so parallel execution is always safe.
Every lane runs in an isolated git worktree. Changes are only merged after validation passes — typecheck, lint, and tests.
Four commands. That's it.
From install to shipping features — Parton stays out of your way.
Install
Analyze
Run
Watch
See it in action.
A real execution run — waves execute in order, lanes run in parallel, and every story is validated before committing.
Run development at any scale.
Parton is free for individual use and always will be. Paid plans add coordination, visibility, and infrastructure for teams.
Free
Everything you need to run Parton locally.
- Local CLI
- Repo analysis
- Dependency graph
- Touch set prediction
- Targeted context
- Wave/lane execution
- Parallel AI execution
- Local artifacts
- Branch output
Team
Coordinate AI-driven development across your team.
- Everything in Free
- Shared run registry
- Conflict detection
- Team scheduler
- Project dashboard
- Run history & analytics
- Team visibility
- Role-based access
- Hosted infrastructure
Enterprise
For organizations that need control, compliance, and scale.
- Everything in Team
- Distributed orchestration
- Advanced scheduler policies
- Enterprise policy controls
- Private infrastructure
- Security & compliance
- Dedicated support
- SLA
- Advanced analytics
- Org governance
Get early access to Pro features.
Team and Enterprise plans are coming soon. Join the waitlist and we'll notify you when they launch.
| Feature | Free | Team | Enterprise |
|---|---|---|---|
| Local CLI | |||
| Targeted context | |||
| Parallel execution | |||
| Team coordination | |||
| Shared run registry | |||
| Conflict detection | |||
| Remote workers | |||
| Enterprise policy engine | |||
| Private infrastructure |
What makes Parton different.
Not another AI code generator — a structured execution engine built for real-world codebases.
AI planning
Automatically decomposes features into right-sized user stories with dependency ordering — no manual breakdown needed.
Parallel execution
Independent stories run simultaneously across isolated git worktrees, cutting feature delivery time by 3–5×.
Repo intelligence
Parton indexes your codebase — file structure, dependencies, patterns — so every AI worker has the right context.
Conflict prevention
A scheduler tracks file touch-sets across lanes and prevents concurrent edits to the same files.
Transparent execution
Every decision, plan, and validation result is logged and visible in the dashboard — no black-box AI.
Get in touch.
Questions about Parton? Enterprise needs? We'd love to hear from you.
Start running development with AI.
Describe a feature. Parton plans, parallelizes, and ships it.