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Description
A new artificial intelligence system has been developed to detect and respond to child sexual abuse material more efficiently, aimed at protecting victims at a faster rate. Utilizing real CSAM data, this AI effectively scans, identifies, and flags new images that depict child abuse with remarkable precision. In partnership with law enforcement and prominent Canadian universities, CEASE.ai employs a combination of neural networks and various AI models to achieve accurate detection of such harmful content. The system offers investigators a user-friendly plugin that allows them to upload images from their cases and run hash lists to filter out known content. Subsequently, the AI suggests potential labels and prioritizes images that may contain previously unseen CSAM. Investigators can then examine the flagged images, verify their illegal nature, strengthen their cases against perpetrators, and expedite the rescue of vulnerable victims. Additionally, social media platforms integrate with the CEASE.ai API endpoint, which processes all user-uploaded images in real time, ensuring that any content related to child abuse is swiftly identified and labeled by the system. This innovative approach not only enhances the efficiency of investigations but also contributes significantly to the protection of children at risk.
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
Two Hat
Founded
2012
Country
Canada
Website
www.twohat.com/cease-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