Label Your Data

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Overview

$1,000+

Min Project Size

< $25/hr

Avg Hourly Rate

250 - 999

Employees

2019

Year Founded

ABOUT LABEL YOUR DATA

Secure Data Annotation for CV and NLP

Label Your Data has been offering secure, high-quality data annotation services for Computer Vision and NLP applications since 2020. We assist Data Scientists and AI Engineers in simplifying the dataset labeling process so they can concentrate on model development. Here are some reasons to select us as your data annotation service provider: We have experience across more than 20 industries, such as Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech, and Insurance. Our primary services include, but are not restricted to, data annotation. Feel free to send us a sample of your dataset to experience our services at no cost.

Languages Spoken

English

HIGHLIGHTS

$1,000+

Min Project Size

< $25/hr

Avg Hourly Rate

250 - 999

Employees

2019

Year Founded

Services

Focus

Industries

Clients

Services Provided

50% Data Annotation Services

50% Generative AI

About the Team

OUR STORY

Operating globally with regional headquarters in the US and EU, our company thrives under the leadership of CEO Karyna Naminas, who brings extensive experience from the outsourcing sector, driving worldwide growth. Co-founder and advisor Daria Leshchenko, recognized among INC's 200 Female Founders, has instilled a strong commitment to delivering exceptional service for over 15 years in tech. Since our inception six years ago, we've earned multiple industry accolades from respected critics like Clutch and Designrush. We proudly serve clients across 22 countries with a dedicated team of 1,000 professionals based in three offices. Our clients consistently praise our flexibility, high-quality data annotation, effective communication, and timely delivery, underscoring our passion for supporting successful projects through innovative data solutions.

Portfolio

OCR of financial documents

We offer top-notch OCR data annotation for both ongoing and on-demand projects. Our annotation services for financial documents encompass a wide range of materials, including invoices, financial statements, insurance papers, checks, and legal documents. Additionally, our team is skilled in labeling documents in 42 different languages, such as Spanish, Polish, German, Portuguese, Czech, Romanian, Slovak, Italian, Japanese, and Korean. Our specialized teams support various intelligent data extraction algorithms, enabling the processing of 1.5 million documents daily.

LiDAR

Label Your Data is proficient in managing various annotation types for LiDAR data, and our expert team is ready to support you with any data-driven LiDAR projects in AI. We primarily utilize Cuboids and Bounding Box annotations for our clients. To deliver the optimal output format tailored to client requirements, our data annotators can operate with either our proprietary LiDAR labeling tools or external tools. Additionally, our skilled annotators are adept at handling complex 3D LiDAR data. For instance, we are currently collaborating with a Canadian firm that employs LiDAR data to create intelligent traffic solutions, a project that has been ongoing for two years. Our annotators utilize the client’s ground truth annotation software and have processed over 90 distinct LiDAR maps, annotating more than 200,000 objects with bounding boxes and cuboid annotations. Furthermore, we have developed a custom output format to align with our client's specifications, simplifying the integration of our annotations into their workflow.

Named Entity Recognition

Label Your Data possesses extensive expertise in conducting annotations for various Named Entity Recognition (NER) tasks across 42 languages. Our team has annotated a significant quantity of data for customer support projects, including up to 50,000 chats focusing on sentiment analysis, as well as for fintech projects involving up to 400,000 bank transactions. In the case of the latter, we have reviewed 400,000 transactions to identify merchant names, classify the transactions (i.e., whether they are business or personal), and highlight details such as addresses, payment methods, and transaction categories.

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