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Description
Patronus AI serves as an advanced platform dedicated to the automated evaluation, security, and optimization of large language model applications and agentic systems. By providing tools that enable teams to deploy AI products efficiently at scale, it facilitates the generation of test suites, execution of experiments, logging of traces, output comparisons, monitoring of production interactions, and real-time assessment of model performance. The platform is equipped with top-tier evaluators that address various concerns, including RAG hallucinations, context integrity, image relevance, accuracy of answers, prompt vulnerabilities, data privacy risks, toxicity, bias, and other critical safety and reliability issues. Additionally, Patronus Evaluators can assign scores to AI outputs based on specific criteria, and teams have the flexibility to design custom evaluators tailored to their unique use cases. The platform integrates a comprehensive suite of features such as dashboards, APIs, ready-to-use evaluations, logs, traces, side-by-side output comparisons, visual analytics, and real-time alert systems, which collectively empower teams to identify errors, benchmark their models, refine prompts, and gain insights into system behavior over time. Ultimately, this holistic approach enhances the overall effectiveness and reliability of AI deployments in various applications.
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
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
Patronus AI
Founded
2023
Country
United States
Website
www.patronus.ai/
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/shieldstral/
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
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