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Description
AIBA, a cybersecurity firm based in Norway, focuses on utilizing AI technology for content moderation across digital platforms, particularly aimed at shielding children and adolescents from various online dangers such as grooming, bullying, and harmful interactions. Their flagship product, Amanda, is an AI-driven moderation solution that aims to protect younger users in online gaming and social networking settings. By using real-time detection methods, Amanda effectively identifies and addresses harmful content, automating responses while allowing more intricate cases to be reviewed by human moderators. Additionally, it provides valuable insights into user behavior and community dynamics, assisting organizations in creating safer and more appealing online environments. With a strong emphasis on regulatory compliance, Amanda is designed to help organizations meet international safety and transparency laws, including the EU's Digital Services Act, COPPA & KOSA in the United States, the Online Safety Bill in the UK, and Australia's Online Privacy Bill, thus ensuring that the platform adheres to the latest safety standards in digital interactions. This comprehensive approach not only protects young users but also promotes a culture of responsibility and awareness among digital platforms.
Description
Shieldstral is an innovative multimodal safety classifier with a 3B parameter open-weight structure, adept at assessing text, images, and combined text-plus-image content based on dynamically defined policies during inference. Rather than adhering to a static set of harm categories, it approaches moderation as a binary question-and-answer format: users submit a contextual instruction outlining the evaluation criteria and strictness, pose a yes-or-no safety inquiry, and present the content for assessment. The model processes the “yes” and “no” logits to generate a continuous, calibrated safety score, enabling applications to prioritize or rank outcomes based on confidence levels instead of relying on a single categorical label. This design effectively integrates prompt classification, response moderation, refusal detection, toxicity assessment, and multimodal safety evaluation into a singular interface, empowering teams to modify policies without the need for model retraining. Shieldstral's versatility allows it to analyze prompts, responses, pairs of prompts and responses, images, and images paired with text, making it a comprehensive tool for safety evaluation. As such, it represents a significant advancement in the field of content moderation.
API Access
Has API
API Access
Has API
Integrations
Mistral AI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
AIBA
Founded
2022
Country
Norway
Website
aiba.ai/
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/shieldstral/
Product Features
Content Moderation
Artificial Intelligence
Audio Moderation
Brand Moderation
Comment Moderation
Customizable Filters
Image Moderation
Moderation by Humans
Reporting / Analytics
Social Media Moderation
User-Generated Content (UGC) Moderation
Video Moderation
Product Features
Content Moderation
Artificial Intelligence
Audio Moderation
Brand Moderation
Comment Moderation
Customizable Filters
Image Moderation
Moderation by Humans
Reporting / Analytics
Social Media Moderation
User-Generated Content (UGC) Moderation
Video Moderation