Product
Label Studio
by HumanSignal
- Product website
- https://labelstud.io
- Documentation
- https://labelstud.io/guide/
- Pricing
- https://humansignal.com/pricing/
- Categories
- Data Labeling & Annotation Datasets Platform
Description
Data labeling platform for annotating machine learning datasets.
AI-native score
How ready this product is for agents to use, on a 0–100 scale across four weighted dimensions. Security is one of them, so a high score is not a substitute for your own security or vendor-risk review. How is this scored?
Research coverage: 58% of the scored decision fields carry a confirmed value. Unresearched fields score zero in the grade above.
| Component | Raw | Weight | Contribution |
|---|---|---|---|
| Integration | 2/10 | 35% | 7.0 |
| Trust | 3/6 | 30% | 15.0 |
| Portability | 4/4 | 20% | 20.0 |
| Security | 2/4 | 15% | 7.5 |
Signals that fired
- Integration: Command-line interface (+1) ; SDK / developer kit (+1)
- Trust: No generative AI training (yes, +2) ; Verified trust center (+1)
- Portability: Data export (partial, +1) ; Data import (partial, +1) ; Open standards (+1) ; Standard protocol access (+1) ; No proprietary-SDK lock-in (+1) ; Self-hostable (+1) ; Open source (+1)
- Security: Compliance certifications (+1) ; Access controls — RBAC / ABAC (+1)
Signals not researched
These gaps cover the fields used in the AI-native score.
- Integration surfaces: llms.txt, Headless signup, MCP servers, Native connectors, API specs, Agent skills
- Trust & data policy: Multi-factor authentication, Zero data retention, Hard budget caps, Sandbox environment, Documented provider swap
Trust & data policy
- Trust center
- Vendor trust center
- No generative AI training
- Yes
- Data export
- Partial
- Data import
- Partial
- Open standards
- Yes
- Standard protocol access
- Yes
- No proprietary-SDK lock-in
- Yes
- Self-hostable
- Yes
- Open source
- Yes
- Source code
- https://github.com/HumanSignal/label-studio
Not yet researched Multi-factor authentication, Zero data retention, Hard budget caps, Sandbox environment, Documented provider swap
Security & compliance
Certifications and access controls this product reports on its own pages. We confirm the vendor lists each one; for certifications we don't audit the underlying report. Part of the 15% security score.
A shared trust or security page can support several certifications. We do not require separate public report links because reports may require login, vendor approval, or a nondisclosure agreement. Ask the vendor for reports and applicable coverage before a procurement decision. These listings expose no per-claim check date; the entry's updated date does not date the supporting evidence.
Compliance certifications
Access controls
What it does
Jobs to be done
-
View 3 productsLabel machine learning data
Annotate data for training or evaluating machine learning models.
-
View 3 productsManage machine learning datasets
Organize and maintain datasets for machine learning development.
Integration surfaces
How an agent connects to this product and finds its documentation. The largest dimension of the AI-native score (35%).
- WebMCP
- No
Command-line interfaces
Developer kits
-
Label Studio Python SDK
Languages: Python
Confirmed absent Agent2Agent (A2A) servers
Not yet researched llms.txt, Headless signup, MCP servers, Native connectors, API specs, Agent skills
Offers
Starter Cloud
$99/mo
No recorded price in this currency
Additional users cost $49 per month each.
View offerReviews
No approved reviews yet.
Catalog activity
Track how this entry changes as proposals are opened and merged.
Related products
Products from other publishers that share a job-to-be-done or category, most-shared first.
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Same job: Label machine learning data (not assessed), Manage machine learning datasets (not assessed)
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Same job: Label machine learning data (not assessed)
-
Same job: Manage machine learning datasets (not assessed)
Ready to decide?
Tier C · 50/100 AI-native · 58% researched.