Alibaba Cloud PAI iTAG vs Argilla

Alibaba Cloud PAI iTAG is a data-labeling platform for image, text, video, audio and multimodal datasets. Built-in image tasks include classification, object detection, OCR, table recognition and semantic segmentation; official templates also cover image-text explanation, conversation ranking, visual question answering and video OCR. Teams can use official or tenant templates, or create templates for business-specific labeling. A job brings together an OSS-backed dataset and template with labels, subtasks, checks, labelers and reviewers. Manual labeling is free, and selected large-model labeling templates are currently free; OSS storage and data transfer are billed separately. Input data must be in Alibaba Cloud OSS, and the workspace and bucket must be in the same region. Dataset imports require an index file rather than a direct path to a folder of raw files. From August 1, 2026, iTAG 1.0 is allowlist-only and in maintenance mode. Existing customers with prior labeling tasks or datasets can continue using current features. New users seeking AI-powered automatic dataset labeling are directed to Multimodal Data Management. API operations include listing, creating, updating and deleting templates and labeling tasks.

Argilla is a free collaboration tool for AI engineers and domain experts building datasets with human feedback. It supports NLP, LLM, and multimodal projects, including classification, named entity recognition, retrieval-augmented generation, and preference tuning. Contributors can provide labels, ratings, rankings, and written responses; annotation tools include filters, AI feedback suggestions, and semantic search. The system handles text and images, while custom fields can represent audio, video, or other content rendered as base64 or HTML. It is compatible with Hugging Face and spaCy, and tutorials cover SetFit and LlamaIndex. Deployment options include Hugging Face Spaces or a local machine or server using Docker Compose. A Python SDK connects to an Argilla server with an API URL and key, and the server exposes REST API documentation. Datasets and records can be moved to or from Python, local disk, and the Hugging Face Hub. Argilla supports OAuth2 through Hugging Face, GitHub, and Google by default. It does not train models; on Hugging Face Spaces, data on ephemeral free storage is lost when the Space restarts.