AI Model Discovery is the process of identifying, locating, and understanding all AI models deployed within an organization, regardless of their physical or logical location. This includes models developed in-house, procured from vendors, open-source models integrated into applications, and those lurking in the shadows across:
Public Clouds: You need to discover all AI models active across platforms like AWS, Azure, GCP, and others, including those in both production and non-production environments.
SaaS Applications: You need to collect comprehensive details on AI models operating within your SaaS applications and internal projects via dedicated assessments. This might involve uncovering LLMs integrated into marketing automation tools or those used for fraud detection in financial applications.
Private Environments: You also need to locate and analyze models running on-premises or in private clouds using various scanning approaches. This could include uncovering custom-built LLMs and other AI models used for specific business goals.
By encompassing all environments, AI Model Discovery fosters a holistic view of your AI landscape, ensuring visibility into every aspect, including the often-overlooked shadow AI, regardless of its type, like an LLM silently processing data in the background.
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