Many organizations begin their GenAI initiatives with the expectation that AI can handle all information within the enterprise. However, in reality, information exists in various formats, including documents, logs, images, conversations, and many more that often contain sensitive personal data, such as national ID numbers, email addresses, phone numbers, customer identifiers, financial account information, or health-related records, all of which require strict privacy and compliance controls. Feeding this data into AI systems without proper controls introduces serious security, compliance, and privacy risks.
Many organizations have long relied on keyword or regex-based detection, but these approaches consistently fall short in both accuracy and coverage. Because they lack contextual understanding, they often miss critical personal information or result too many false positives, resulting in noisy outputs that undermine AI usability. Since these methods rely primarily on text parsing, they cannot adequately process unstructured formats such as images, scanned documents, or system logs, creating gaps that slow down AI adoption.
What organizations need is not another “one-size-fits-all” foundation model, but a purpose-built system that can precisely detect and securely de-identify personal information based on the actual characteristics of their enterprise data.
Fasoo AI-R Privacy x AnalyticDID is built specifically for this need.
With Fasoo, organizations achieve more than basic personal data protection. They gain
Ultimately, the goal is not to build a “perfect, all-purpose AI,” but to transform how personal information is governed so it can be safely used in AI environments. AI-R Privacy × AnalyticDID provides the practical, real-world solution to make that shift possible.
