Data labelling companies, products & suppliers
Human or AI-assisted annotation of training and eval data. Jobs: annotation uis; workforce or vendor labelling; qa of labels.
What is Data labelling?
Human or AI-assisted annotation of training and eval data. Jobs: annotation uis; workforce or vendor labelling; qa of labels.
What problems does it solve?
Supervised models and evals need labelled examples you can defend.
Typical business use cases
- Annotation UIs
- Workforce or vendor labelling
- QA of labels
Important capabilities
- Taxonomies
- Annotator workflow
- Agreement metrics
What buyers should evaluate
- Who sees the raw data
- Workforce location
- Gold-set process
Risks and governance considerations
Sensitive records shown to an unmanaged labelling workforce.
Procurement checklist
- Workforce terms
- Access
- Gold set
Relevant AI Trustmark assurance
AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.
Companies and providers
Claimed suppliers appear first so buyers can start with listings the company has taken ownership of. Payment does not buy this order.
Amazon Web Services is Amazon's cloud division selling compute, storage, Bedrock model hosting and related AI infrastructure. Public pages cover regional cloud services for builder
Appen delivers expert human data for training and evaluating AI models, with long-standing annotation and collection services. Appen publishes Appen Human Data as named AI products
Turn raw images, videos, and 3D data into model-ready datasets with CVAT. Use AI-assisted annotation, quality control, analytics, collaboration tools, APIs, and expert labeling ser
Datature is an end-to-end platform for data labeling, model training, and deployment. It empowers enterprises and developers to build Vision AI models faster. Datature publishes Da
Encord is the multimodal data layer for physical AI. Manage, curate, annotate, and align petabytes of data - from sensor streams to video to text. Trusted by 300+ AI teams includin
Labeling, evaluation, and quality workflows that deploy where your data lives and scale with the world. HumanSignal publishes Label Studio Enterprise as named AI products. HumanSig
Scalable feedback that integrates into your data flywheel. Kognic publishes Kognic Platform as named AI products. Kognic is used for Data labelling work. Kognic publishes product i
From environments to custom evaluations, we partner with over 90% of leading AI labs in the US and the innovators defining the next frontier of AI. Labelbox publishes Labelbox Mode
Labellerr provides high-quality, scalable data labeling for AI and ML. Get reliable annotation services to train accurate machine learning models. Labellerr is used for Data labell
Segments.ai BV sells a data-labeling platform for images, video and sensors. Public pages describe annotation workflows for machine-learning teams, not caption generation. Segments
SuperAnnotate publishes SuperAnnotate as a named AI product. SuperAnnotate is used for Data labelling work. SuperAnnotate publishes product information at superannotate.com. SuperA
Products
Claimed products appear first. Ranking packs and payment do not change this list.
- Amazon SageMaker Ground Truth· Amazon Web Services
- Appen Human Data· Appen
- CVAT Enterprise· CVAT.ai
- Datature Vi· Datature
- Encord Annotate· Encord
- Kognic Platform· Kognic
- Label Studio Enterprise· HumanSignal
- Labelbox Annotate· Labelbox
- Labellerr· Labellerr
- Segments.ai· Segments.ai
- SuperAnnotate· SuperAnnotate
Also used in this category
These products have a different primary category so they do not compete for the same ranking queries. They are listed here because buyers still encounter them in this job.
- Labelbox Model-Assisted Labeling· Labelbox
Related categories
Relevant procurement and assurance guides
Frequently asked questions
What is Data labelling?
Human or AI-assisted annotation of training and eval data. Jobs: annotation uis; workforce or vendor labelling; qa of labels.
What should not be listed as Data labelling?
Products whose buyer job is active learning controllers, synthetic data, or prep tools. Those belong on their own category page so search queries are not split.
Has AI Trustmark independently assessed every Data labelling supplier?
No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.
What model or provider changes should a buyer insist on being told about?
Material change usually includes a new model family, new region, new subprocessor, new write-capable tool, or a change that affects logging, privacy or human oversight. Those changes should trigger evidence refresh rather than a silent release.
How should buyers verify where AI customer data is processed?
Ask for the named processing locations, cloud regions and any subprocessors that see prompts, files or outputs. A directory listing is not evidence of residency. Independent assessment records the locations that were in scope on the assessment date.
Does a TrustMark on one product cover the rest of the company?
No. Independent assessment is scoped to the named organisation and, where relevant, the named product. Category pages list suppliers as a topic label. They do not imply that every listed company has been assessed.
What incident-handling evidence is useful for AI suppliers?
Buyers should see how AI-specific failures are detected, contained and notified — including unsafe outputs, data leakage and unauthorised agent actions. An incident policy that never mentions models, prompts or tools is incomplete for this class of product.
What security testing evidence should buyers request for an AI product?
Ask what was tested, against which version, whether prompt-injection, data-exfiltration and tenant isolation were in scope, and where failed prompts were stored. A generic ISO certificate or a vendor scanner screenshot is not by itself an AI TrustMark assessment.