Versioning Training Data in Unitlab: Reproducible Releases for ML Teams
A release-engineering playbook for training data: what to version, how to approve changes, and how to connect Unitlab releases to model experiments.
Building Multimodal Datasets for AI: Image, Video, Audio, Text, and Documents
A practical architecture for assembling multimodal training data in Unitlab without losing identity, alignment, schema clarity, or release lineage.
Datasets vs. Releases in Unitlab: What to Use, When, and Why
A practical decision guide to Unitlab datasets and releases: working collections for active operations versus versioned handoffs for downstream use.
How to Connect Cloud Storage to Unitlab
See the actual Unitlab connection screens, the credentials each provider needs, and a safe way to validate a cloud-backed annotation source.
Data Curation in Unitlab: Assets, Filters, Folders, and Embedding Views
A hands-on data-curation playbook for turning raw assets into representative, reviewable, and reproducible working datasets in Unitlab.
Documents and Multimodal Releases: Building Rich Training Data in Unitlab
A live-product look at document data in Unitlab, multimodal release anatomy, verified capabilities, and a reproducible handoff pattern for ML teams.
Text Annotation in Unitlab: Entities, Relations, and Structured Context
How to structure entity and relation annotation in Unitlab, resolve span ambiguity, calibrate reviewers, and create reusable NLP training data.
Audio Annotation in Unitlab: Events, Segmentation, and Speech Workflows
A practical operating guide for audio events, temporal boundaries, transcription-oriented projects, quality review, and versioned delivery in Unitlab.
Multimodal Data Annotation in One Workspace: A Complete Unitlab Tour
A live-product tour of Unitlab's multimodal data operations—from source assets and reusable ontologies to review workflows and versioned releases.