Enable AI Innovation Without Losing Control of Your Data
Agentic AI can improve productivity, accelerate decision-making, and automate complex workflows. But before granting AI access to enterprise data, organizations should understand the risks that come with increased autonomy.
Before you deploy another AI agent, ask these questions:
Do you have visibility into where sensitive data resides across cloud and on-premises repositories?
Are sensitive documents classified before AI systems can retrieve them?
Are AI-generated documents protected after they are created and shared?
Can you revoke access to sensitive information after it leaves your environment?
Could an employee accidentally expose confidential information through an AI prompt?
Do you know what your AI agents can access, and can you stop them from reaching data they shouldn’t?
Are your AI initiatives aligned with compliance and governance requirements?
If you cannot confidently answer any of these questions, your organization may have hidden AI data exposure risks that traditional security controls cannot address.
Unlike traditional software applications, AI agents continuously interact with enterprise data. They search repositories, access documents, retrieve historical information, generate responses, and share outputs across users and systems. This creates new risks that traditional security controls were never designed to address.
Many organizations do not know where sensitive information resides across file shares, cloud storage platforms, collaboration systems, and user devices. If AI agents can access this data, they can potentially expose information that was never intended for AI consumption.
Employees may unintentionally submit confidential information to ChatGPT, Microsoft Copilot, Claude, Gemini, or other AI tools. Customer records, intellectual property, financial information, source code, and strategic plans can all become part of AI interactions.
Even when AI tools are used appropriately, the resulting documents and reports often contain sensitive information that must remain protected after creation. Traditional access controls stop working once files are downloaded, copied, shared, or stored outside controlled environments.
Securing Agentic AI requires visibility and protection throughout the entire AI data lifecycle. Organizations must understand what data exists, identify what is sensitive, control how AI systems interact with it, and ensure information remains protected after AI-generated content is created.
Before organizations can secure AI, they need to understand what data exists and where it resides. Sensitive data is often scattered across file shares, cloud storage, collaboration platforms, and endpoint devices. Without visibility, organizations risk exposing confidential information to AI systems without realizing it.
Fasoo Data Radar helps organizations discover, classify, and tag sensitive information across enterprise environments, enabling security teams to establish governance policies before data is accessed by AI tools and agents.
Key Capabilities:
Not all data should be accessible to AI systems.
Once sensitive information has been identified, organizations should apply protection controls to ensure only authorized users and systems can access critical data. This reduces the risk of sensitive information being exposed through AI-powered search, retrieval, or analysis.
Fasoo Data Radar automatically identifies sensitive content, while Fasoo Enterprise DRM applies persistent encryption and access controls to protected files. Organizations can selectively encrypt confidential documents, intellectual property, regulated information, and other high-value assets without disrupting business operations.
Key Benefits:
Even with strong data governance, employees acn unintentionally expose sensitive information through AI interactions. Prompts submitted to ChatGPT, Microsoft Copilot, Claude, Gemini, and other AI tools may contain customer information, source code, financial data, business strategies, or intellectual property. Organizations need visibility into how AI tools are being used and controls to prevent sensitive information from being shared.
Fasoo AI-R DLP monitors AI interactions in real time and evaluates prompts before information is submitted to generative AI platforms. When sensitive content is detected, organizations can block, warn, monitor, or audit AI activity based on the sensitivity of the information involved.
Supported Use Cases:
AI-generated content can be just as sensitive as the data used to create it.
Reports, summaries, analyses, presentations, and business documents generated by AI often contain confidential information that remains valuable long after creation. Without persistent protection, these files can be copied, shared, or distributed without control.
Fasoo Enterprise DRM ensures that AI-generated content remains protected wherever it travels. Security policies stay with the file, allowing organizations to control access, monitor usage, revoke permissions, and maintain visibility even after documents leave managed environments.
Capabilities Include:
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Protect your sensitive data before it reaches AI systems.
Agentic AI refers to AI systems that can independently plan, reason, and take actions to achieve specific goals with limited human intervention. Unlike traditional AI assistants that simply respond to prompts, AI agents can access data, interact with applications, execute tasks, and make decisions across multiple workflows. As organizations adopt Agentic AI to improve productivity and automation, securing the data these systems can access and use becomes increasingly important.
Agentic AI security refers to the controls and governance practices used to protect data accessed, processed, or generated by AI agents. Unlike traditional applications, AI agents can interact with multiple systems, retrieve enterprise knowledge, and make decisions autonomously, creating new risks around data exposure and misuse.
AI systems can only be governed effectively when organizations understand what data exists and where it resides. Sensitive information hidden across file shares, cloud storage, collaboration platforms, and endpoints may be unintentionally exposed if it is not identified and classified before AI access is enabled.
Organizations can use AI-aware data loss prevention (DLP) solutions to monitor AI interactions and evaluate prompts before information is submitted. Security teams can then block, warn, or audit prompt activity when sensitive data such as customer records, intellectual property, or financial information is detected.
Traditional DLP solutions were designed primarily for email, web uploads, and file transfers. Agentic AI introduces new interaction models that require visibility into prompts, AI-generated content, and autonomous data access, making AI-specific governance and monitoring increasingly important.
AI-generated documents, reports, and summaries often contain sensitive business information that remains valuable long after creation. Persistent protection technologies such as Enterprise DRM help organizations maintain access control, usage visibility, and protection wherever those files are stored or shared.
Fasoo AI combines data discovery, classification, AI-aware DLP, and persistent document protection to secure information throughout the AI lifecycle. By helping organizations discover sensitive data, control AI interactions, and protect content after creation, Fasoo AI enables secure and scalable AI adoption.
