Data Labeling Services for Every Data Type
Reliable, Cost-Effective General Data Annotators for Your AI Projects
Managed teams label your images, video, audio, and text with the accuracy and consistency that model training demands. Offshore rates. No long-term lock-in.
What Data Labeling Is
Data labeling is the work of tagging raw data so machine learning models can learn from it. The terms data labeling and data annotation describe the same work. General labeling covers the four core data types: images, video, audio, and text. Managed labeling teams deliver higher consistency than crowd platforms because the same trained annotators work on your project from start to finish.
Built for Teams Training on Core Data Types
- Computer vision teams labeling image and video datasets
- Natural language processing (NLP) and chatbot builders
- Autonomous systems and robotics companies
- Media and content platforms tagging at scale
- Startups scaling past founder-labeled data
Four Data Types, One Managed Team
- Image labeling: bounding boxes, polygons, semantic segmentation, landmarks, and classification.
- Video labeling: frame-by-frame object tracking, activity recognition, and event tagging.
- Audio labeling: speech labeling, transcription, speaker tagging, and sentiment.
- Text labeling: categorization, keyword tagging, entity recognition, and intent labeling.
Why Consistency Beats Crowdsourcing
Crowd platforms route your data to anonymous workers who change with each batch. Each worker leaves with knowledge of your guidelines, and label consistency drifts. Our model is different: a dedicated team learns your guidelines once, labels your project end to end, and improves with every feedback cycle. You manage the team directly inside your tools, with our quality oversight behind them.
Layered Review on Every Batch
Senior annotators review samples from every batch. We track inter-annotator agreement and report accuracy against acceptance targets you set. A dedicated Client Success Manager oversees the engagement at no added cost.
Three Steps to a Working Team
Scope
We review your data types, volume, and guidelines in a free consultation.
Build
We staff and train your dedicated team against your labeling guidelines.
Deliver
Your team labels using your tools with our quality oversight. Scale up or down as the project moves.
Scope
We review your data types, volume, and guidelines in a free consultation.
Build
We staff and train your dedicated team against your labeling guidelines.
Deliver
Your team labels using your tools with our quality oversight. Scale up or down as the project moves.
FAQ Section
What is the difference between data labeling and data annotation?
None in practice. Data labeling and data annotation refer to the same work: tagging raw data so machine learning models learn from it. Some teams use labeling for simpler tags and annotation for richer markup, but vendors and buyers use the terms interchangeably.
What data types do you label?
Images, video, audio, and text. Image work covers bounding boxes, polygons, segmentation, landmarks, and classification. Video covers object tracking and activity recognition. Audio covers transcription, speaker tagging, and sentiment. Text covers categorization, entities, and intent.
How is a managed team different from a crowd platform?
Crowd platforms send your data to anonymous workers who change constantly, so guideline knowledge and consistency drift. A managed team learns your guidelines once, works on your project end to end, and improves with feedback. You manage the team directly, with our quality oversight behind them.
What annotation tools do your teams work in?
Yours. Teams work inside your labeling platform and follow your workflow. Annotators arrive familiar with standard annotation tools, so onboarding to your stack is fast.
How much do data labeling services cost?
Labeling teams typically run $1,700 to $2,500 per annotator per month. Where you land in the range depends on the annotator’s expertise and the complexity of your data. We quote rates per annotator during scoping, with no long-term lock-in.
How fast will my labeling team be ready?
Most teams are scoped, staffed, and trained within weeks, not months. The timeline depends on team size, data complexity, and the maturity of your labeling guidelines. We share a staffing plan with dates during your free consultation.
Start With a Strong Labeling Foundation
Tell us your data types and volume. We will show you the team, the quality process, and the pricing before you commit.