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Geberit Quotes

After running pilots with several annotation providers, Label Your Data delivered the strongest results by a clear margin, standing out on turnaround time, annotation quality, and the responsiveness of their feedback loops.

Quotes
Geberit
Maxime Debarbat

Maxime Debarbat

Senior ML Engineer (GenAI)

Trusted by ML Professionals

Ouster
Searidge Technologies
Zendar
Advanced Farm
ABB
Toptal
UiPath
Respeecher
Yale
Thorvald

Video Labeling Services

Label your video datasets with certified security and a free pilot offer.

RUN FREE PILOT

Trusted by 200+ Customers

ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX

Who We Serve

ML Engineers

ML Engineers

Building video-based ML models for action detection or object tracking

Building video-based ML models for action detection or object tracking

Facing delays with in-house data labeling

Facing delays with in-house data labeling

Dataset Providers

Dataset Providers

Selling labeled video datasets

Selling labeled video datasets

Need fast, accurate video labeling to meet demand

Need fast, accurate video labeling to meet demand

AI-Powered Business

AI-Powered Business

Using ML for video analysis or surveillance

Using ML for video analysis or surveillance

Struggling with large volumes of raw footage

Struggling with large volumes of raw footage

Academic Researchers

Academic Researchers

Requiring labeled video datasets for studies

Requiring labeled video datasets for studies

Have limited time for complex labeling tasks

Have limited time for complex labeling tasks

Discuss your challenges

Check Your Video Labeling Needs

Localizing and classifying objects quickly, works for well-defined objects.

Making detailed shapes when accuracy is critical.

Working with 3D objects and environment to label data in three dimensions.

Tracking fine details such as facial features, skeletal structures, or joint positions.

Making precise pixel-level classification when it is important, but individual object distinction is not needed.

Segmenting when you need to differentiate between individual objects that belong to the same category.

Segmenting when you need both pixel-level classification and individual instance differentiation in complex scenes.

Localizing and classifying objects quickly, works for well-defined objects.

Making detailed shapes when accuracy is critical.

Working with 3D objects and environment to label data in three dimensions.

Tracking fine details such as facial features, skeletal structures, or joint positions.

Making precise pixel-level classification when it is important, but individual object distinction is not needed.

Segmenting when you need to differentiate between individual objects that belong to the same category.

Segmenting when you need both pixel-level classification and individual instance differentiation in complex scenes.

How It Works

Step 1

Free Pilot

Send your video dataset for free labeling and assess our services risk-free.

Step 2

QA

Assess the pilot results to confirm they align with your quality standards and budget.

Step 3

Proposal

Receive a customized proposal for your specific video labeling needs.

Step 4

Start Labeling

Begin the video labeling process with our skilled global team.

Step 5

Delivery

Get your labeled videos delivered on time, ensuring your ML project stays on track.

Calculate Your Cost
Estimates line

1 Select labeling method
2 Specify how many objects to process
3 Check the approximate total cost
4 Run free pilot
Select Labeling Method
Amount
0 1M
Estimated Cost
$ x entities
$
RUN FREE PILOT

Send your sample data to get the precise cost FREE

Reviews

What Our Clients Say

"Their flexibility and ability to move fast impress us."

Label Your Data has successfully collected data from public sources, annotated missing skeletons, and validated pre-annotations for almost 15,000 images. Although their instructions are sometimes unclear, the team has received praise for their flexibility and speed. They also communicate via email.

"Although the task is unusual and difficult, their annotation quality is incredible."

Label Your Data has delivered high-quality data labels, which have received positive client feedback. Their team produces outputs on time and solves challenges without upselling. They also communicate effectively through virtual meetings.

“I'm impressed with how easy our communication with the team is and how simple and effective the processes are."

Label Your Data's support has been crucial in developing the client's computer vision perception algorithms. They lead a simple and effective collaboration by responding quickly to concerns and questions and delivering everything on time.

"The Label Your Data team was always available for questions."

Label Your Data provided the client with high-quality annotations and added to the number of annotations in the client's portfolio. The team was consistently available for questions or updates that needed to be added to the data set. The client was impressed with the team's communication skills.

"Their flexibility and ability to work with multiple languages are impressive."

Label Your Data continues to work diligently for the client. They consistently provide training data for different document types and languages. Furthermore, they are excellent communicators and collaborators, and their ability to serve high-quality services is outstanding.

"They were always ready to work whenever we had projects."

After engaging with Label Your Data, the client has seen a reduction in error rate and success with model accuracy running on production. The team delivered on time and was communicative in their approach. The client was impressed with the steps Label Your Data took to ensure accurate QA testing.

Why AI Teams Choose Label Your Data

Data Annotation for Complex Environments

Data Annotation for Complex Environments

Rely on consistent, high-quality output for complex datasets, detailed taxonomies, and edge cases.

Structured Quality from Pilot to Production

Structured Quality from Pilot to Production

Get quality engineered into every step through onboarding, evolving guidelines, QA, and continuous feedback.

Flexible and Scalable Operations

Flexible and Scalable Operations

Adjust team capacity, project size, and delivery model as you scale, with no setup fees or long-term lock-ins.

An Integrated Delivery Partner

An Integrated Delivery Partner

Align on goals, workflows, and expectations with a team that integrates into your process from day one.

Projects Led by Annotation Experts

Projects Led by Annotation Experts

Work with former annotators who understand annotation complexity, quality standards, and high-volume delivery.

Request a pilot

Tell us more about your project and data

Email is not valid.

Email is not valid

Company name is not valid

Phone is not valid

Some error text

Thank you for contacting us!

Thank you for contacting us!

We'll get back to you shortly

Geberit Quotes

After running pilots with several annotation providers, Label Your Data delivered the strongest results by a clear margin, standing out on turnaround time, annotation quality, and the responsiveness of their feedback loops.

Quotes
Geberit
Maxime Debarbat

Maxime Debarbat

Senior ML Engineer (GenAI)

Trusted by ML Professionals

Ouster
Searidge Technologies
Zendar
Advanced Farm
ABB
Toptal
UiPath
Respeecher
Yale
Thorvald

FAQs

What is video labelling?

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Video labeling is the process of tagging objects, people, or actions within a video, frame by frame. This helps ML models learn to recognize and track things, like identifying cars in traffic or detecting activities in security footage.

How to annotate video data?

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Before starting, our team is trained on the project instructions and software. Then, we label targeted elements—like objects or actions—throughout the video, frame by frame. This includes drawing boxes, tagging actions, or marking key points to ensure accuracy and consistency for the machine learning model.

RUN FREE PILOT