Data Labeling Services

Outsource data labeling to professionals

Trusted by 100+ Customers

Use Cases for

ML Engineers

Tackling supervised learning/RLHF projects

Facing delays with in-house annotations

Dataset Business

Offering annotated datasets for sale

Need rapid processing of raw data

AI-Powered Business

Implementing ML models for object recognition

Struggling to manage growing data volumes

Academic Researchers

Required to provide annotated data for peer review

Have limited time for annotation tasks

Discuss your challenges

Data Services for You

Computer Vision Annotation

Computer Vision Annotation

NLP Annotation

NLP Annotation

QA & Model Validation

QA & Model Validation

LLM Fine Tuning

LLM Fine Tuning

Data Collection

Data Collection

Content Moderation

Content Moderation

Data Processing

Data Processing

An image of a frog, used as an example of a rectangle-based image annotation

An image of a frog, used as an example of a polygon-based image annotation

An image of a frog, used as an example of a 3D cuboid-based image annotation

An image of a frog, used as an example of a keypoint-based image annotation

An image of a frog, used as an example of an instance segmentation annotation applied to an image

An image of a frog, used as an example of a semantic segmentation annotation applied to an image

An image of a frog, used as an example of a panoptic segmentation annotation applied to an image

Rectangles

Polygons

Cuboids

Keypoints

Instance segmentation

Semantic segmentation

Panoptic segmentation

Lidar / Radar

Pick the service you need

An example of text classification depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. Each word is annotated as a part of speech like noun or verb

An example of named entity recognition depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. Frodo is annotated as a name, the frog as an animal, and the tree as a location

An example of sentiment analysis depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. The words determined and hopeful are annotated as positive, while the word slowly crawled is annotated as neutral

An example of sentence comparison depicted as an image of 2 sentences. The first sentence is: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. The second sentence is: Sam the toad, feeling anxious and tired, climbed the tree in search of shelter

An example of audio to text transcription depicted as a sound wave like in the audio editor software. Some parts of the wave are annotated to show what’s being said

Text Classification

Named Entity Recognition

Sentiment Analysis

Comparison

Audio-To-Text Transcription

Pick the service you need

An example of a data annotation edge case depicted as a bird next to a flower that looks like a bird. But the flower is wrongfully recognized as a bird with 92% accuracy

An example of an object recognition of a bird with 98% accuracy

Quality Assurance

Model Validation

Pick the service you need

An example of 2 LLMs generating different inferences for data annotator to choose the best response

An example of one LLM generating two different inferences for data annotator to choose the best one

An example of a user submitting a detailed prompt with a detailed response from the LLM

An example of a user requesting the LLM to generate an image of a green truck. The LLM responses with the correctly generated image

An example of a user requesting the LLM to depict the image. The LLM correctly guesses the description

An image example of semantic segmentation with a title: train your LLM like Segment Anything to annotate objects on images

LLM Comparison

Question-Answer Pairs

Prompts Generation

Image and Text Alignment

Image Captioning

Object Detection and Classification

Pick the service you need

Request to gather publicly available or field data.

Pick the service you need

An example of content moderation: identified NSFW content on social media. It is censored and labeled as NSFW.

Get a dedicated content moderator or annotate your NSFW social data to train your model.

Pick the service you need

Beyond annotation, process your data with services like digitizing, parsing, and cleansing.

Pick the service you need

Computer Vision Annotation

Computer Vision Annotation

An image of a frog, used as an example of a rectangle-based image annotation

An image of a frog, used as an example of a polygon-based image annotation

An image of a frog, used as an example of a 3D cuboid-based image annotation

An image of a frog, used as an example of a keypoint-based image annotation

An image of a frog, used as an example of an instance segmentation annotation applied to an image

An image of a frog, used as an example of a semantic segmentation annotation applied to an image

An image of a frog, used as an example of a panoptic segmentation annotation applied to an image

Rectangles

Polygons

Cuboids

Keypoints

Instance segmentation

Semantic segmentation

Panoptic segmentation

Lidar / Radar

Pick the service you need

NLP Annotation

NLP Annotation

An example of text classification depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. Each word is annotated as a part of speech like noun or verb

An example of named entity recognition depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. Frodo is annotated as a name, the frog as an animal, and the tree as a location

An example of sentiment analysis depicted as an image of the sentence: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. The words determined and hopeful are annotated as positive, while the word slowly crawled is annotated as neutral

An example of sentence comparison depicted as an image of 2 sentences. The first sentence is: Frodo the frog, determined and hopeful, slowly crawled up the tree, seeking a safe heaven. The second sentence is: Sam the toad, feeling anxious and tired, climbed the tree in search of shelter

An example of audio to text transcription depicted as a sound wave like in the audio editor software. Some parts of the wave are annotated to show what’s being said

Text Classification

Named Entity Recognition

Sentiment Analysis

Comparison

Audio-To-Text Transcription

Pick the service you need

QA & Model Validation

QA & Model Validation

An example of a data annotation edge case depicted as a bird next to a flower that looks like a bird. But the flower is wrongfully recognized as a bird with 92% accuracy

An example of an object recognition of a bird with 98% accuracy

Quality Assurance

Model Validation

Pick the service you need

LLM Fine Tuning

LLM Fine Tuning

An example of 2 LLMs generating different inferences for data annotator to choose the best response

An example of one LLM generating two different inferences for data annotator to choose the best one

An example of a user submitting a detailed prompt with a detailed response from the LLM

An example of a user requesting the LLM to generate an image of a green truck. The LLM responses with the correctly generated image

An example of a user requesting the LLM to depict the image. The LLM correctly guesses the description

An image example of semantic segmentation with a title: train your LLM like Segment Anything to annotate objects on images

LLM Comparison

Question-Answer Pairs

Prompts Generation

Image and Text Alignment

Image Captioning

Object Detection and Classification

Pick the service you need

Data Collection

Data Collection

Request to gather publicly available or field data.

Pick the service you need

Content Moderation

Content Moderation

An example of content moderation: identified NSFW content on social media. It is censored and labeled as NSFW.

Get a dedicated content moderator or annotate your NSFW social data to train your model.

Pick the service you need

Data Processing

Data Processing

Beyond annotation, process your data with services like digitizing, parsing, and cleansing.

Pick the service you need

How It Works

Step 1

Free Pilot

Submit your dataset for free labeling and test our services without risk.

Step 2

QA

Assess the pilot output to ensure it meets your quality and budget needs.

Step 3

Proposal

Receive a proposal customized to your specific data labeling needs.

Step 4

Start Labeling

Begin the labeling process with our expert team to advance your ML project.

Step 5

Delivery

Get your labeled data delivered promptly, ensuring your project stays on track.

Calculate Your Cost
Estimates

1 Pick application field

2 Select labeling method

3 Specify how many objects to label

4 Check the approximate total cost

5 Run free pilot

Pick Application Field

Select Labeling Method

Keypoints

Rectangles

Polygons

Cuboids

Amount

0 1M

Estimated Cost

$ x objects

$

Select Labeling Method

Entities to label

Characters in a dataset

Annotation hours

Amount

0 1M

Estimated Cost

$ x entities

$

For other use cases

send us your request to receive a custom calculation

Send your sample data to get the precise cost FREE

Reviews

What Our Clients Say

Clutch

Clutch

ClutG2 Crowdch

ClutG2 Crowdch

"We were impressed by the labeled data quality as well."

Label Your Data makes significant progress toward the goal of enhancing the client’s algorithm performance. The team works quickly to deliver annotations and annotators with extensive experience in the field. Their project management is straightforward, making for a smooth engagement.

Roman Lutsyshyn

Roman Lutsyshyn

CEO, NLP Development Company

"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

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

LYD showed high quality and flexibility and convinced us from day one with their high passion for delivering a great service. We currently evaluate further possibilities to further involve them in our initiatives and projects.

Luca van Skyhawk

Luca van Skyhawk

VP of Customer Success, Hypatos GmbH

“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.

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.

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 2020. Their expertise shows productive results as the project progresses.

Asad Lesani

CEO, Blue City Technology

Why Projects Choose Label Your Data

No Commitment

Check our performance based on a free trial

Flexible Pricing

Pay per labeled object or per labeling hour

Tool-Agnostic

Working with every labeling tool, even your custom tools

Data Compliance

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

Start Free Pilot

fill up this form to send your pilot request

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We'll get back to you shortly

Label Your Data were genuinely interested in the success of my project, asked good questions, and were flexible in working in my proprietary software environment.

Kyle Hamilton

PhD Researcher at TU Dublin

Trusted by ML Professionals

FAQs

Do I need to commit to a long-term contract?

Not at all. We offer 3 flexible pricing options:

Short term for one-off projects like academic research
On-demand for seasonal projects when you need additional workforce
Long term for a streamlined data annotation workflow

What is your pricing?

We calculate according to how much time is spent on your object annotation. That’s why the pilot project is also valuable for us – we get to calculate the expenses

When can I start the free pilot?

As soon as we clarify details on your dataset. You’ll get a reply within this or the next work day.

Do you work with our labeling tools?

Absolutely! We’re flexible with any tools you want us to work in.

How can I trust you with my confidential data?

We earned several data compliance certificates to prove our dedication to data security:

PCI DSS Level 1
ISO:27001
GDPR
CCPA

After we sign the NDA, we make sure to anonymize your data for our employees to prevent any data leaks.

What are data labelling services?

It’s a service where people annotate/tag/label visual or text data. The clients use this data to sell it or train an Al model.

How do I label my data?

To label your data, you’ll first need to choose the right annotation method and labeling tool, depending on the data type you work with. This process is often time-consuming and complex to handle in-house, but Label Your Data makes it easier. They offer secure data labeling services with a global team of experts, and you can start with a free pilot to see how it works for you.