People For AI Reviews & Ratings

People For AI

5.0 out of 5 stars

Ratings and Reviews 14 Ratings

Total 5 out of 5 stars
ease 4.5 out of 5 stars
features 4.5 out of 5 stars
design 4.5 out of 5 stars
support 5 out of 5 stars

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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What is People For AI?

People For AI specializes in data labeling services designed to deliver exceptional datasets for the training of computer vision, natural language processing, or speech recognition systems. Our advanced AI-driven tools are specifically adapted to meet the unique requirements of your project, ensuring that your data is meticulously handled with the appropriate technology, skilled personnel, and effective strategies. We prioritize long-term labelers, which allows us to excel in providing high-quality data annotation, but we are also equipped to handle a diverse range of projects. For further information about our dedicated team of labelers and our comprehensive services, please explore our website. Additionally, we pride ourselves on maintaining a rigorous quality assurance process to guarantee the highest standards in data labeling.

What is Label Your Data?

Our organization stands out as the leading provider of data labeling services tailored for AI applications. We serve a diverse array of sectors including Automotive, Robotics, Fintech, Healthcare, E-commerce, Manufacturing, and Insurance. With a dedicated team of over 500 annotation specialists and support in multiple languages, we deliver precise and efficient services catering to both enterprise-level and R&D initiatives. Our offerings encompass a wide range of services such as Computer Vision and NLP annotation, comprehensive data processing, and beyond. By choosing Label Your Data, you can expect unmatched excellence in the quality of your training datasets. We prioritize the security and integrity of our clients' data above all else. To uphold the confidentiality of client information, our facilities and personnel have received certifications from ISO 27001 and PCI DSS (level 1), demonstrating our commitment to industry-leading security. Additionally, we strictly comply with essential industry regulations such as GDPR and CCPA, ensuring that your data remains protected at all times. Our unwavering dedication to quality and security makes us the ideal partner for your data labeling needs.

Media

No images available

Media

Integrations Supported

Kili Technology
Labelbox
SuperAnnotate
V7 Darwin

Integrations Supported

API Availability

API Availability

Pricing Information

Free trials are available,
POC project (under 1000€) are availables.
Production project begin from 200 hours of labeling.
Free Trial Offered?

Pricing Information

Flexible Business Models For Any Project Size:
- for enterprises and medium-sized businesses
- for project-based data annotation needs
- for academia, POC projects or any short-term data annotation orders
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

People For AI

Date Founded

2020

Company Location

France

Company Website

peopleforai.com

Company Facts

Organization Name

Label Your Data

Date Founded

2019

Company Location

USA

Company Website

labelyourdata.com

Categories and Features

Data Annotation

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
Team Collaboration

Categories and Features

Data Annotation

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Image Annotation

Not specified

Video Annotation

Not specified

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