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features
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support

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Description

Jozu functions as an AI-driven platform focused on securing supply chains by validating artifacts prior to their execution, managing agent activities in real-time, and maintaining a record of all actions taken afterward. The Jozu Hub acts as a self-hosted repository for models, agents, MCP servers, and skills, ensuring that each artifact is consolidated with cryptographic signatures, attestations, thorough scanning, policy regulations, and audit trails. This platform's security analysis, tailored specifically for AI, addresses various threats including concealed executable code within model packages, compromised weights, data poisoning, prompt injection, insecure tools, and violations of licensing. Users can create policies once, which are then distributed as signed OCI artifacts, and these policies are enforced during the processes of pulling, promoting, admitting, or executing artifacts. Additionally, Jozu Agent Guard operates in conjunction with workloads across servers, desktops, edge devices, and isolated systems, implementing local filtering for prompts and input-output, access controls for tools, requirement for approvals, and enforcement of policies in real-time. Through this comprehensive approach, Jozu not only enhances security but also ensures a robust framework for managing and safeguarding AI-related artifacts throughout their lifecycle.

Description

Llama Guard is a collaborative open-source safety model created by Meta AI aimed at improving the security of large language models during interactions with humans. It operates as a filtering mechanism for inputs and outputs, categorizing both prompts and replies based on potential safety risks such as toxicity, hate speech, and false information. With training on a meticulously selected dataset, Llama Guard's performance rivals or surpasses that of existing moderation frameworks, including OpenAI's Moderation API and ToxicChat. This model features an instruction-tuned framework that permits developers to tailor its classification system and output styles to cater to specific applications. As a component of Meta's extensive "Purple Llama" project, it integrates both proactive and reactive security measures to ensure the responsible use of generative AI technologies. The availability of the model weights in the public domain invites additional exploration and modifications to address the continually changing landscape of AI safety concerns, fostering innovation and collaboration in the field. This open-access approach not only enhances the community's ability to experiment but also promotes a shared commitment to ethical AI development.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon EKS Yes 
Amazon Elastic Container Registry (ECR) Yes 
Azure Kubernetes Service (AKS) Yes 
Databricks Yes 
Docker Yes 
GitHub Actions Yes 
GitLab Yes 
Google Kubernetes Engine (GKE) Yes 
Hugging Face Yes 
JFrog Artifactory Yes 
Jenkins Yes 
Kubeflow Yes 
Kubernetes Yes 
Llama No 
MLflow Yes 
Model Context Protocol (MCP) Yes 
Nebius Token Factory No 
OpenAI No 
Sonatype Nexus Repository Yes 
VMware Tanzu Yes 

Integrations

Amazon EKS No 
Amazon Elastic Container Registry (ECR) No 
Azure Kubernetes Service (AKS) No 
Databricks No 
Docker No 
GitHub Actions No 
GitLab No 
Google Kubernetes Engine (GKE) No 
Hugging Face No 
JFrog Artifactory No 
Jenkins No 
Kubeflow No 
Kubernetes No 
Llama Yes 
MLflow No 
Model Context Protocol (MCP) No 
Nebius Token Factory Yes 
OpenAI Yes 
Sonatype Nexus Repository No 
VMware Tanzu 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 No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Jozu

Founded

2023

Country

United States

Website

jozu.com

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/

Product Features

Product Features

Alternatives

Alternatives

Llama 3 Reviews

Llama 3

Meta