The goal is to unlock sensitive data values by delivering security that is seamless across the data lifecycle, removing bottlenecks that slow innovation while keeping data usable for analytics and AI.

Capital One Software executives emphasize secure-by-default protection to eliminate security bottlenecks and support enterprise AI initiatives without compromising sensitive data.

The overarching objective is secure-by-default data lifecycle protection that preserves semantic structure for analytics and AI workflows while removing barriers to AI adoption.

A fully self-hosted deployment option for regulated organizations is now available, along with enhanced protection policies featuring granular access controls and a centralized token analytics dashboard for system visibility.

New deployment and governance enhancements include a 100% self-hosted option for regulated environments, stronger protection policies with granular access controls, and a centralized token analytics dashboard to monitor health and throughput.

Upcoming features include continued emphasis on self-hosted deployment for regulated settings, advanced protection policies with granular access controls, and a centralized token analytics dashboard for performance visibility.

Readers are invited to visit RSAC booth numbers and explore the Databolt product page for more details.

Databolt will soon inspect unstructured data—PDFs, emails, transcripts, and Office documents—to identify and protect personal data using tokenization that preserves semantic context for AI and analytics.

Updates focus on protecting unstructured data by analyzing formats and applying tokenization to maintain semantic structure for analytics and AI workflows.

Databolt will automatically identify and protect PII in unstructured formats through tokenization and related techniques to reduce exposure.

Upcoming data catalog connectivity will improve metadata collection for integration across complex data stacks.

Industry context notes that about 40% of chief product officers are open to granting AI agents meaningful autonomy, underscoring the need for secure data to advance AI initiatives.