Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
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