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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
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Label Studio
✓ verifiedFreemium
Open-source data-labeling and AI-evaluation platform for image, text, audio, video and LLM workflows, with a paid enterprise tier.
261K visits/mo
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Super Annotate
✓ verifiedPaid
Enterprise data-annotation and evaluation platform pairing a labeling tool with a managed expert annotator workforce.
406K visits/mo
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The New GitBook
✓ verifiedFreemium
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
653K visits/mo2.9K saves
Pricing
Starter: $99/user/mo (up to 12 users, hosted)
Free trial available
No public pricing
No public pricing
Free trial available
Core features
- ✦Open-source multi-type labeling
- ✦Programmable, customizable interfaces
- ✦API, SDK and webhooks
- ✦ML backend for pre-labeling and active learning
- ✦LLM evaluation and RLHF workflows
- ✦Enterprise QA, SSO and analytics
- ✦Customizable multimodal annotation editors for image, video, text and audio
- ✦Support for RLHF preference data, SFT datasets, RAG and agent evaluation workflows
- ✦Managed expert annotator workforce option
- ✦Data curation, exploration and analytics tools
- ✦Team and project management with SSO on higher tiers
- ✦Integrations with AWS, GCP, Databricks, Snowflake and others
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
Use cases
- →Labeling training data across modalities
- →Human-in-the-loop AI evaluation
- →RLHF and fine-tuning data collection
- →RAG and LLM benchmarking
- →Building large-scale labeled datasets to train computer vision or NLP models
- →Running human evaluation and RLHF pipelines for LLM fine-tuning
- →Auditing and scoring AI agent decisions with human review
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
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