# Iterations

An iteration is a recurring work cycle within a phase, primarily used to log assets (models, datasets, graphs, and notes) to document the work and maintain transparency throughout an AI project.

### Why use iterations?

* Empower Data Scientists to achieve goals, evaluate results, and refine methods with feedback. 
* Facilitate informed decision-making, knowledge capture, and enhanced collaboration. 
* Ensure progress preservation, build trust in AI projects, and enable time-saving through efficient [iterative developments](https://docs.vectice.com/24.4/glossary/concepts/iterations/iterative-development).

<table><thead><tr><th width="185">Features</th><th>Description</th></tr></thead><tbody><tr><td><strong>Seamless creation via API</strong></td><td>Iterations are exclusively created through the Vectice API</td></tr><tr><td><strong>Ownership and asset logging</strong></td><td>Each iteration has an owner who solely can log assets via the Vectice API</td></tr><tr><td><strong>Starred iterations</strong></td><td>Iterations can be highlighted with a star to signify their importance, drawing attention to key assets or information within the iteration.</td></tr><tr><td><strong>Organize iteration work</strong></td><td>Users can organize iterations into sections within the Vectice app, allowing for a tailored presentation of their iteration progress and the work completed.</td></tr></tbody></table>