White-Label Annotation for
Software Agencies

Offer data labeling to your ML clients and unlock a new revenue stream.

Trusted by 100+ Customers

Solve Your Challenges

Agency Owners

Add a new revenue stream

Upsell labeling as an extra service for ML clients

ML Engineers

Prepare labeled datasets for client models

Keep building without pausing dev work or switching tools

Data Annotation Types Supported

Rectangles

Rectangles

Polygons

Polygons

Cuboids

Cuboids

Keypoints

Keypoints

Semantic segmentation

Semantic segmentation

Instance segmentation

Instance segmentation

Panoptic segmentation

Panoptic segmentation

An example of object detection depicted as a bird in a rectangle labeling

An example of a labeled facial recognition image, where the face is in the rectangle

An example of a labeled vehicle detection image, where the bus is in the rectangle

An example of a labeled product identification image, where the product is in the rectangle

Object detection

Facial recognition

Vehicle detection

Product identification

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

An example of a labeled autonomous driving image, where the car and traffic lights are labeled using polygons.

An example of a labeled satellite imagery, where the landfill is labeled using polygons.

An example of a labeled medical imaging, where the heart is labeled using polygons

Autonomous driving

Satellite imagery

Medical imagery

Making detailed shapes when accuracy is critical.

An example of a labeled autonomous vehicles image, where the cars are labeled using cuboids.

An example of a labeled robotics image, where the warehouse boxes are labeled using cuboids.

An example of a labeled spatial mapping image, where the room is labeled using grid and cuboids.

Autonomous vehicles

Robotics

Spatial mapping

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

An example of a labeled facial landmark image, where the face is labeled using keypoints.

An example of a human pose estimation, where the person’s body is labeled using keypoints.

An example of a labeled emotion image, where the face is labeled using keypoints.

An example of a labeled hand gesture image, where the hands are labeled using keypoints.

Facial landmarks

Human pose estimation

Emotion recognition

Hand gesture tracking

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

An example of a labeled road segmentation image, where the road is processed via semantic segmentation

An example of a labeled medical imaging where it is processed via semantic segmentation

An example of a labeled land use classification, where the landfill is processed via semantic segmentation

Road segmentation

Medical imaging

Land use classification

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

An example of labeled crowd analysis image, where it is processed via instance segmentation

An example of 5 labeled apple images to learn the model how to count, where it is processed via instance segmentation

Crowd analysis

Counting objects

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

An example of a panoptic segmentation in data annotation

An example of a panoptic segmentation in data labeling

Rectangles

Rectangles

An example of object detection depicted as a bird in a rectangle labeling

An example of a labeled facial recognition image, where the face is in the rectangle

An example of a labeled vehicle detection image, where the bus is in the rectangle

An example of a labeled product identification image, where the product is in the rectangle

Object detection

Facial recognition

Vehicle detection

Product identification

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

Polygons

Polygons

An example of a labeled autonomous driving image, where the car and traffic lights are labeled using polygons.

An example of a labeled satellite imagery, where the landfill is labeled using polygons.

An example of a labeled medical imaging, where the heart is labeled using polygons

Autonomous driving

Satellite imagery

Medical imagery

Making detailed shapes when accuracy is critical.

Cuboids

Cuboids

An example of a labeled autonomous vehicles image, where the cars are labeled using cuboids.

An example of a labeled robotics image, where the warehouse boxes are labeled using cuboids.

An example of a labeled spatial mapping image, where the room is labeled using grid and cuboids.

Autonomous vehicles

Robotics

Spatial mapping

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

Keypoints

Keypoints

An example of a labeled facial landmark image, where the face is labeled using keypoints.

An example of a human pose estimation, where the person’s body is labeled using keypoints.

An example of a labeled emotion image, where the face is labeled using keypoints.

An example of a labeled hand gesture image, where the hands are labeled using keypoints.

Facial landmarks

Human pose estimation

Emotion recognition

Hand gesture tracking

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

Semantic segmentation

Semantic segmentation

An example of a labeled road segmentation image, where the road is processed via semantic segmentation

An example of a labeled medical imaging where it is processed via semantic segmentation

An example of a labeled land use classification, where the landfill is processed via semantic segmentation

Road segmentation

Medical imaging

Land use classification

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

Instance segmentation

Instance segmentation

An example of labeled crowd analysis image, where it is processed via instance segmentation

An example of 5 labeled apple images to learn the model how to count, where it is processed via instance segmentation

Crowd analysis

Counting objects

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

Panoptic segmentation

Panoptic segmentation

An example of a panoptic segmentation in data annotation

An example of a panoptic segmentation in data labeling

Features

Explore The Platform

Seamless Execution

Cost Calculator

Instruction Generator

Free Task

API Access

Team Access

Label Your Data platform: uploading dataset

Seamless Execution

Upload client data, set rules, and get labeled results with no extra steps.

Label Your Data platform: cost calculator

Cost Calculator

Calculate your cost so you can add markup before quoting your client.

Label Your Data platform: instruction generator

Instruction Generator

Turn your client’s brief into clear guidelines using a pre-made template.

Label Your Data platform: free pilot task

Free Task

Test a small job for free before offering it as part of your service.

Label Your Data platform: API access

API Access

Connect your internal tools to automate client data upload and output.

Label Your Data platform: team access

Team Access

Invite colleagues or clients to manage work and assign access as needed.

How It Works

Step 1

Create a project based on your client’s needs.

Step 2

Run a free task to test the setup.

Step 3

Upload the remaining data.

Step 4

Track your project’s progress.

Step 5

Download your completed annotations.

Reviews

What Our Clients Say

Clutch

Clutch

ClutG2 Crowdch

ClutG2 Crowdch

"They’re willing to drop everything to fulfill our needs and keep us happy."

Demonstrating a profound dedication to the project, Label Your Data consistently provides near-perfect deliverables at a cost-effective price. Thanks to their help, the client has been able to be more flexible with their work. Their impressive turnaround time further enhances the solid partnership.

Jack Hopkins

CTO, Raveler Ltd

“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.

Piotr Swierczynski

Piotr Swierczynski

Director of Engineering, NODAR

"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.

Josha Bharadwa

Software Architect, Searidge Technologies

"They are flexible, dedicated, and their processes are well organized."

Label Your Data sends out weekly data annotation for the client to review. So far, the platform hasn’t had any issues and they are focusing on enhancing the platform since it was launched in November 2024. Their expertise shows productive results as the project progresses.

Asad Lesani

CEO, Blue City Technology

Why Projects Choose Label Your Data

No Need to Commit

Check our performance based on a free task.

Profit-Friendly

Resell data labeling with project pricing starting at $100.

Plug & Play

Focus on your development, while we coordinate annotators and tools.

Data-Compliant

Work with a data-certified vendor: PCI DSS Level 1, ISO:2700, GDPR, CCPA.

Join Our Happy Customers

FAQs

What is data labeling, and who needs it?

Data labeling is the process of tagging raw data (like images, videos, or text) with information that machine learning models can learn from. It’s a critical step in building supervised ML systems.

ML teams need labeled data to train models to recognize patterns, make predictions, or detect objects. That includes use cases like object detection, facial recognition, sentiment analysis, and more.

If you’re an agency building ML models, offering labeled data as part of your service helps them move faster without doing it in-house. And for you, it’s a clear upsell.

Who will be labeling our client data?

Your data is labeled by a trained workforce, managed by experienced QA specialists to ensure accuracy and consistency.

Can I invite my client to the platform?

Yes. You can give your client limited access to track progress or review tasks. Some agencies use this to stay transparent, others charge a separate fee for managing the project through the platform. It’s optional; you can also handle everything in-house and just deliver the results.

Will my client see Label Your Data anywhere?

No, unless you give them access. You can run the entire project under your own name and brand. White-labeling is fully supported.

Can I label just a small part of the dataset to start?

Yes. You can break large projects into stages or run a small batch first. It’s useful for pilots or when working with limited budgets.

Can I use my client’s annotation guidelines?

Yes. You can upload your own instructions or use the built-in template to quickly adapt client briefs into clear, actionable tasks.

What file formats do you support?

We work with image, video, 3D point cloud, and geospatial data. Our platform supports all standard formats across these types, so you can upload what you already have. No conversions needed.

If you're unsure about a specific format, just ask and we’ll confirm right away.

How is annotation quality checked?

Every task goes through a multi-step QA process handled by trained reviewers. You can request samples, give feedback, and ask for revisions at any stage to match your client’s requirements.