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DeepSentinel
Secure AI Workflows with Affordable Privacy.

What is DeepSentinel?

DeepSentinel provides a comprehensive platform designed to secure and manage Artificial Intelligence (AI) workflows. It focuses on delivering robust security measures, ensuring compliance with various regulations, and maintaining seamless performance for AI operations. The platform offers real-time threat detection for data transactions, enabling users to identify and address potential attacks proactively, thereby reducing operational risks before they escalate.

The service emphasizes granular control over AI workflows through customizable policies, ensuring both security and operational efficiency. DeepSentinel incorporates advanced input and output scanning to protect sensitive data, prevent threats, and facilitate compliant AI experiences. Its infrastructure is built for scalability, allowing businesses to grow while maintaining high security standards, including role-based access control (RBAC). The platform also supports integration with existing AI and cloud systems via APIs for smooth implementation.

Features

  • Real-time threat monitoring: Detect attacks and protect data before they become issues with instant visibility on suspicious activities.
  • Granular Control: Maintain visibility and control over AI workflows with customizable security policies.
  • Advanced Data Protection: Utilizes input and output scanning to protect sensitive data and prevent threats.
  • AI-Powered Compliance Monitoring: Scans and verifies compliance with regulations like GDPR, HIPAA, SOC 2.
  • API & Workflow Integration: Facilitates easy integration with existing AI and cloud platforms via APIs.
  • Security & Scalability: Offers a robust, scalable infrastructure with advanced RBAC for secure growth.

Use Cases

  • Securing AI workflows in financial institutions.
  • Ensuring regulatory compliance (GDPR, HIPAA, SOC 2) for AI applications.
  • Protecting sensitive data processed by AI models.
  • Monitoring AI data transactions for threats in real-time.
  • Integrating security layers into existing AI and cloud infrastructures.

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