People For AI Reviews & Ratings

People For AI

5.0 out of 5 stars
OORT DataHub Reviews & Ratings

OORT DataHub

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 13 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 4.5 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 OORT DataHub?

Our innovative decentralized platform enhances the process of AI data collection and labeling by utilizing a vast network of global contributors. By merging the capabilities of crowdsourcing with the security of blockchain technology, we provide high-quality datasets that are easily traceable. Key Features of the Platform: Global Contributor Access: Leverage a diverse pool of contributors for extensive data collection. Blockchain Integrity: Each input is meticulously monitored and confirmed on the blockchain. Commitment to Excellence: Professional validation guarantees top-notch data quality. Advantages of Using Our Platform: Accelerated data collection processes. Thorough provenance tracking for all datasets. Datasets that are validated and ready for immediate AI applications. Economically efficient operations on a global scale. Adaptable network of contributors to meet varied needs. Operational Process: Identify Your Requirements: Outline the specifics of your data collection project. Engagement of Contributors: Global contributors are alerted and begin the data gathering process. Quality Assurance: A human verification layer is implemented to authenticate all contributions. Sample Assessment: Review a sample of the dataset for your approval. Final Submission: Once approved, the complete dataset is delivered to you, ensuring it meets your expectations. This thorough approach guarantees that you receive the highest quality data tailored to your needs.

Media

No images available

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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

Please contact us to get a quote on pricing

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / 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

OORT DataHub

Company Location

United States

Company Website

www.oortech.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

AI Development

Not specified

AI Infrastructure

Not specified

Blockchain

Not specified

Crowdsourcing

Not specified

Data Annotation

Not specified

Data Collection

Not specified

Data Labeling

Not specified

RLHF

Not specified

Web Dataset Providers

Not specified

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