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What is Jozu?

Jozu serves as an AI-powered platform dedicated to enhancing the security of supply chains by confirming the integrity of artifacts before they are executed, overseeing agent activities in real-time, and keeping a detailed log of all subsequent actions. The Jozu Hub functions as a self-contained repository for models, agents, MCP servers, and skills, guaranteeing that each artifact is integrated with cryptographic signatures, attestations, comprehensive scans, policy compliance, and audit records. This platform's security assessment, specifically designed for AI applications, tackles numerous threats such as hidden executable code within model packages, compromised weights, data poisoning, prompt injection, insecure tools, and licensing breaches. Users can establish policies once, which are then distributed as signed OCI artifacts, with enforcement occurring during the actions of pulling, promoting, admitting, or executing these artifacts. Furthermore, Jozu Agent Guard collaborates seamlessly with workloads across servers, desktops, edge devices, and isolated systems, applying local filtering for prompts and input-output, implementing access controls for tools, requiring approvals, and enforcing policies in real-time. By adopting this all-encompassing strategy, Jozu significantly boosts security while also providing a resilient framework for managing and protecting AI-related artifacts throughout their entire lifecycle. Ultimately, this ensures that users can trust the integrity and compliance of their AI systems.

What is Amazon Bedrock Guardrails?

Amazon Bedrock Guardrails serves as a versatile safety mechanism designed to enhance compliance and security for generative AI applications created on the Amazon Bedrock platform. This innovative system enables developers to establish customized controls focused on safety, privacy, and accuracy across various foundation models, including those hosted on Amazon Bedrock, as well as fine-tuned or self-hosted variants. By leveraging Guardrails, developers can consistently implement responsible AI practices, evaluating user inputs and model outputs against predefined policies. These policies incorporate a range of protective measures like content filters to prevent harmful text and imagery, topic restrictions, word filters to eliminate inappropriate language, and sensitive information filters to redact personally identifiable details. Additionally, Guardrails feature contextual grounding checks that are essential for detecting and managing inaccuracies or hallucinations in model-generated responses, thus ensuring a more dependable interaction with AI technologies. Ultimately, the integration of these safeguards is vital for building trust and accountability in the field of AI development while also encouraging developers to remain vigilant in their ethical responsibilities.

Media

Media

Integrations Supported

Amazon EKS
Amazon Elastic Container Registry (ECR)
Azure Kubernetes Service (AKS)
Databricks
Docker
GitHub Actions
GitLab
Google Kubernetes Engine (GKE)
Harbor
Hugging Face
JFrog Artifactory
Jenkins
Kubeflow
Kubernetes
MLflow
Model Context Protocol (MCP)
Noma
Red Hat OpenShift
Sonatype Nexus Repository
VMware Tanzu

Integrations Supported

Amazon EKS
Amazon Elastic Container Registry (ECR)
Azure Kubernetes Service (AKS)
Databricks
Docker
GitHub Actions
GitLab
Google Kubernetes Engine (GKE)
Harbor
Hugging Face
JFrog Artifactory
Jenkins
Kubeflow
Kubernetes
MLflow
Model Context Protocol (MCP)
Noma
Red Hat OpenShift
Sonatype Nexus Repository
VMware Tanzu

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Jozu

Date Founded

2023

Company Location

United States

Company Website

jozu.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/bedrock/guardrails/

Categories and Features

Categories and Features

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