Preamble
Preamble's AI Safety and Security Platform is an integrated solution designed to streamline and enhance the management of AI systems within an organization. It offers a centralized hub for managing people, overseeing diverse data labeling projects, providing clear guidelines for consistent data labeling, and tracking all labels and datasets.
The platform also facilitates the evaluating of custom models and serves as a comprehensive center for AI safety and security testing and policy deployment. From real-time engagement with AI models to rigorous policy testing, the platform combines these multifaceted components to ensure alignment with organizational values, ethical principles, and compliance standards. Whether it's managing individual roles, conducting adversarial testing, or deploying safety controls, Preamble's platform offers a cohesive and user-friendly environment that addresses the complex and evolving needs of AI safety and security.
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Protecto
While enterprise data is exploding and scattered across various systems, oversight of driving privacy, data security, and governance has become very challenging. As a result, businesses hold significant risks in the form of data breaches, privacy lawsuits, and penalties. Finding data privacy risks in an enterprise is a complex, and time-consuming effort that takes months involving a team of data engineers. Data breaches and privacy laws are requiring companies to have a better grip on which users have access to the data, and how the data is used. But enterprise data is complex, so even if a team of engineers works for months, they will have a tough time isolating data privacy risks or quickly finding ways to reduce them.
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Mindgard
Mindgard is the leader in AI red teaming, helping enterprises identify, assess, and mitigate real-world security risks across AI models, agents, and applications. Founded on pioneering research in AI security, Mindgard was built on the insight that traditional application security approaches cannot protect systems that are probabilistic, adaptive, and deeply embedded into business workflows.
As organizations deploy GenAI and agentic systems at scale, risk increasingly emerges from how AI behaves, what it connects to, and how attackers can manipulate those interactions. Mindgard addresses this challenge with an attacker-aligned approach that mirrors how real adversaries perform reconnaissance, map attack surfaces, exploit system behavior, and pivot through tools, data, and infrastructure. Rather than testing models in isolation, Mindgard evaluates full AI systems in context to surface vulnerabilities with real security impact.
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Cisco AI Defense
Cisco AI Defense is a comprehensive security solution designed to enable enterprises to safely develop, deploy, and utilize AI applications. It addresses critical security challenges such as shadow AI—unauthorized use of third-party generative AI apps—and application security by providing full visibility into AI assets and enforcing controls to prevent data leakage and mitigate threats. Key components include AI Access, which offers control over third-party AI applications; AI Model and Application Validation, which conducts automated vulnerability assessments; AI Runtime Protection, which implements real-time guardrails against adversarial attacks; and AI Cloud Visibility, which inventories AI models and data sources across distributed environments. Leveraging Cisco's network-layer visibility and continuous threat intelligence updates, AI Defense ensures robust protection against evolving AI-related risks.
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