NOMINATION HIGHLIGHTS

InnerActiv represents a fundamental breakthrough in AI data protection by solving what traditional governance platforms cannot see: what actually happens at the endpoint before data enters AI systems. While conventional tools monitor applications and networks after encryption, InnerActiv analyzes data in its original form at the source, providing unprecedented visibility into how sensitive information interacts with AI across every channel, from web-based chatbots to agentic AI workflows to on-machine AI applications.

This endpoint-first architecture enables organizations to track specific data types and their associated risk levels as they move through actual workflows. Security teams can observe in real time when financial data, intellectual property, or personal health information enters an AI prompt, regardless of whether employees use sanctioned enterprise AI, unauthorized shadow AI tools, or locally installed AI applications. This comprehensive coverage closes the visibility gap that allows insider threats and data loss to flourish undetected, even within internally allowed AI accounts where employees may inadvertently or intentionally expose sensitive data.

InnerActiv establishes practical AI guardrails that strike a balance between innovation and security. Blocking AI entirely isn’t realistic in today’s competitive environment, yet allowing unrestricted access creates unacceptable risk. The platform offers granular control over AI data transactions, allowing organizations to establish boundaries that safeguard sensitive information while maintaining productivity. When risky behavior occurs, InnerActiv can block the transaction immediately, preventing data loss before it happens.

The platform delivers complete analytical intelligence through comprehensive risk scoring for all aspects of user activity and usage, bringing high-risk actions to the forefront. Security teams can prioritize their response to the most critical threats while leadership gains visibility into which departments rely on AI, which tools employees actually use versus what’s officially sanctioned, and critically, what types of data flow into these AI systems. These insights enable organizations to identify shadow AI risks and make informed decisions about AI governance policies based on actual employee behavior.

What makes this achievement award-worthy is the combination of depth and breadth. InnerActiv connects monitoring, classification, and control at the endpoint where work actually happens, tracking how specific data elements move through workflows and interact with various AI platforms. Organizations using InnerActiv have discovered unauthorized AI usage that exposed confidential information, detected insider threat patterns involving AI tools, and gained the visibility needed to establish effective AI governance programs grounded in real-world usage data rather than assumptions.