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features
design
support

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Description

Effortlessly anonymize faces, license plates, bodies, and vehicles with our user-friendly solution that seamlessly integrates across all platforms. Address privacy concerns for a diverse array of commercial and industrial applications. Leading global companies place their confidence in our products and expertise as we tackle anonymization issues, allowing you to concentrate on your primary business objectives. Our dedicated team is committed to supporting you throughout your privacy enhancement process. With a strong emphasis on Data Protection, we implement robust measures to ensure compliance with GDPR and other relevant data protection regulations. You have the option to utilize our cloud service for all processing needs, or deploy our Docker container within your on-premise or private/public cloud environments. Our pricing structure is based on a fee per image or video hour, and we offer a demo account that allows you to test our services free of charge. In just seconds, you can blur faces, license plates, individuals, and vehicles in images using a straightforward REST call, making privacy protection both efficient and accessible. By choosing our solution, you not only safeguard sensitive information but also streamline your operations for better efficiency.

Description

Shaip is a comprehensive AI data platform delivering precise and ethical data collection, annotation, and de-identification services across text, audio, image, and video formats. Operating globally, Shaip collects data from more than 60 countries and offers an extensive catalog of off-the-shelf datasets for AI training, including 250,000 hours of physician audio and 30 million electronic health records. Their expert annotation teams apply industry-specific knowledge to provide accurate labeling for tasks such as image segmentation, object detection, and content moderation. The company supports multilingual conversational AI with over 70,000 hours of speech data in more than 60 languages and dialects. Shaip’s generative AI services use human-in-the-loop approaches to fine-tune models, optimizing for contextual accuracy and output quality. Data privacy and compliance are central, with HIPAA, GDPR, ISO, and SOC certifications guiding their de-identification processes. Shaip also provides a powerful platform for automated data validation and quality control. Their solutions empower businesses in healthcare, eCommerce, and beyond to accelerate AI development securely and efficiently.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) Yes 
Docker Yes 
Google Cloud Platform Yes 
Microsoft Azure Yes 
NVIDIA DRIVE Yes 

Integrations

Amazon Web Services (AWS) No 
Docker No 
Google Cloud Platform No 
Microsoft Azure No 
NVIDIA DRIVE No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Celantur

Country

Germany

Website

www.celantur.com

Vendor Details

Company Name

Shaip

Country

United States

Website

www.shaip.com

Product Features

Product Features

Data Labeling

Human-in-the-loop No 
Labeling Automation No 
Labeling Quality No 
Performance Tracking No 
Polygon, Rectangle, Line, Point No 
SDK No 
Supports Audio Files No 
Task Management No 
Team Collaboration No 
Training Data Management No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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