For the complete documentation index, see llms.txt. This page is also available as Markdown.
Data overview
Understand Data Space as the durable source and curation layer.
Data Space is where Unitlab keeps durable source resources independent from any one project. It supports ingestion, folders, lifecycle state, metadata, tags, grouping, filters, embeddings, similarity, duplicates, and outlier analysis.
Use this area when: you need to bring data into Unitlab, organize it, understand its distribution, or prepare an exact cohort for a dataset.
How this area fits into production
Unitlab Data Space Asset library
The Asset library separates folders from individual assets and supports list, grid, and embedding views for different operational questions.
What this area controls
Start with the right page
Decision
Production guidance
Bring in new data
Use Data upload or Cloud providers.
Organize durable resources
Use Data folders and Data assets.
Prepare a cohort
Use Data curation, metadata, tags, filters, and embeddings.
Preserve context
Use Data Groups and custom layouts.
Operating boundary
Data lifecycle state is not project workflow state.
A saved filter is personal navigation state, not immutable dataset membership.
Grouping changes the unit of work; validate it before project attachment.
A production-ready handoff
The selected source cohort is processed, inspected, explainable, and ready to become a published dataset version.
Product context
Unitlab helps AI teams curate, annotate, manage, version, and prepare multimodal training data at enterprise scale.
