Human-Powered data labeling services in New York

Data Labeler specializes in offering accurate, convenient, customized, expedited, and quality-labeled datasets for Machine Learning and AI initiatives.

Increase your competitive advantage | Unlimited support | Exponential growth

Data Labeler specializes in creating quality labeled datasets for machine learning and AI initiatives.

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Our Services

Creating quality labeled datasets for machine

  • Highly accurate labeled data
  • Get options for real-time labeling
  • Guidance on labeling instruction
  • Easily scalable
  • Sophisticated workforce management software
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Our Resources

Creating quality labeled datasets for machine

  • One-stop shop for labeling and training
  • Cost-effective solution for high-quality labels
  • Highly efficient and trusted labeling partner
  • Constant quality checks
  • High flexibility in importing and exporting data

WHY US

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No minimum purchase and spend requirements

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Industry specific workforce

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Global client base

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Quality assurance features

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Flexible, feasible and customizable

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Empowering underserved communities

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Unlimited Support to ensure your datasets meet your expectations

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Join us as a Labeling Partner or Become a Reseller

Data Labeler specializes in creating, Sustainable growth

50

Customers

We are proud to say that we have a huge and ever-growing client base, spanning across the entire globe.

10

Industries

We cater to multiple industries thereby covering a massive footprint.

200

Projects

We have undertaken over 200 plus projects with a dedicated team and by offering flexible solutions.

5

Countries

We cater to an international audience, well equipped to handle challenges and creating a foothold for our brand.

The biggest influence of AI application in our healthcare system is to minimize our time and ease the efforts needed to examine and diagnose the patients. It increases the ability of our healthcare professionals to better understand the day-to-day patterns and needs of the people.

Data Labeler team helped us in providing the solutions with their services. We highly recommend them!

Jack Bony Health Care

The implementation of AI technologies could provide us with the opportunity to make better decisions that increase efficiency in crop and livestock production.

DL created labeling for monitoring cattle and their activities like eating, drinking around the clock, alerting our farmers to notice changes in behavior that might otherwise be easily missed.

Daniel Robert Agriculture

We wanted to use AI for our sector and came across Data Labeler through a friend. They understand our needs and provide solutions!

By using Machine Learning and AI, our Insurance Company can analyze historical data and identify a set of patterns, which is used to detect frauds at an early stage and prevent them, and the insurance experience of our customers transformed from slow, tedious to something fast, easier and on-demand.

Amelia George Insurance

Press & Awards

We have a team of more than 1000 (and growing) full time Data Labelers. Data Labeler specializes in creating, Sustainable growth

Our Services

Bounding box annotation helps in object detection, localization, and classification in videos and images. It helps to identify objects by drawing a box around the objects within an image.

Bounding Boxes

Bounding boxes are generally used for image annotations, they offer the next level of accuracy for multiple industries for developing the object recognition perception models. There are multiple use cases for this, the image annotation technique helps the self-driving vehicles recognize their surroundings, to identify the level of damage, making it easier to calculate insurance claims, recognition of various fashion accessories and furniture.

Data labeler is dedicated to delivering the next level of training data for AI and ML backed with bounding box annotation techniques.

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Polygons

Polygons are multipoint annotation techniques to draw shapes, curves and various angles. Polygons help to annotate objects in angled photos and polygons. They mark category annotations for pixels in an image and also label them.

This also has multiple use cases like, identifying street sign boards, facial and pose features in sports analytics, teaching drones to easily navigate through trees and roofs, tackle new horizons in manufacturing and health-care.

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Points

Key Points are used to detect small objects and shape variations by creating dots across the image.

This helps with detecting and labeling facial/ skeletal features, expressions, emotions, human body parts, poses, and landmarks that might match your task.

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Texts

Algorithms use large amounts of annotated data to train AI and ML models. During the annotation process, a metadata tag is used to mark up attributes of a dataset. With regards to text annotation, that data includes tags such as keywords, phrases, or sentences.

Text annotation helps machines to recognize the crucial words in a sentence making it more meaningful and understandable. Annotations for text include a wide range of types, such as relationship, intent, semantic, and sentiment. Data labelers make sure that these tags are accurate and comprehensive. As poorly annotated text can result in issues in clarity or grammatical errors, or lack of clarity.

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Select

We offer datasets that empower your models to characterize an image and classify it efficiently and effectively.

The Data Labeler can categorize photos and images at a large scale with a high level of accuracy and efficiency.

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Semantic Segmentation

Semantic Segmentation is understanding an image at the pixel level and is used in computer-vision based applications that require high accuracy. This classification is when there are more than two categories in which the images can be classified.

This means an image belongs to more than one category and involves the prediction of multiple labels simultaneously associated with a single instance.

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