Curate Labs builds practical AI systems for operators.
This GitHub organization is where we publish the open-source work that supports that mission.

• Website: curatelabs.ai
• Product work: Products
• Research and writing: Perspectives
• Contact: Get in touch

• Core libraries and integrations from our AI product work
• Workflow and knowledge-graph infrastructure used in real operator environments
• Tooling, examples, and reference implementations that make applied AI easier to ship
• Issues and discussions that reflect real product constraints, not toy problems

We welcome contributions from builders who like solving practical problems in public.

1. Read the repository README and open issues.
2. Pick an issue with clear scope, or propose one with a concrete problem statement.
3. Share your approach early (issue comment or draft PR) before large implementation work.
4. Open a focused PR with tests, documentation, and rationale for key decisions.

• Problem clarity: You define the user or operator problem and why the change matters.
• Execution quality: You ship working code with sensible structure, tests, and edge-case handling.
• Communication: You explain tradeoffs, ask good questions, and respond well to feedback.
• Product judgment: You prioritize usefulness, reliability, and maintainability over novelty.
• Ownership: You follow through, improve docs, and leave the repo better than you found it.

• Keep changes scoped and reviewable.
• Include tests or a clear validation plan.
• Update docs when behavior or APIs change.
• Add context in the PR description: problem, approach, tradeoffs, and follow-ups.

• Be respectful, direct, and constructive.
• Assume positive intent and focus on improving the work.
• Prefer clear reasoning over volume of comments.

Follow updates through our website and product pages:

• Curate Labs
• Products
• Perspectives