Alibaba Cloud PAI iTAG vs Prodigy
Alibaba Cloud PAI iTAG
help.aliyun.comProdigy
prodigy.aiSide by side
| Figure | Alibaba Cloud PAI iTAG | Prodigy |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 2 |
| Spec score · AI Data Labeling Tools | 8.3 (#4) | 8.3 (#6) |
| Founded | 2009 | 2016 |
| Support | The iTAG overview points users to its FAQ and an Alibaba Cloud AI assistant for product, solution, and documentation questions. | The product includes documentation and access to a support forum; company licenses also include priority forum and email support. |
Plans
In their own words
Alibaba Cloud PAI iTAG
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.
Prodigy
Prodigy is a downloadable developer tool and Python library for creating training and evaluation data for machine-learning models. Its built-in recipes cover named entity recognition, text classification, computer vision, audio and video annotation, transcription, and model training and evaluation. A customizable web application offers 23 interfaces for work with text, images, audio, video, relations, multiple choice, HTML and conflict resolution. Users can define workflows with Python recipes and create interfaces using HTML, CSS and JavaScript. Prodigy supports spaCy, plugins for Hugging Face models and integrations with major LLM API providers. Data can be stored in SQLite, MySQL or PostgreSQL and exported to JSON. It runs on the user's own machines without connecting to the maker's or third-party servers, including on air-gapped machines. The standard Python web server and app can be deployed in the cloud or on-premise. Personal licensing costs $390, paid once, excluding tax; Company licensing costs $490, paid once per seat in packs of five, excluding tax.