AI era data security with Capital One Software & Snowflake

Generative AI is redefining how businesses compete—enabling new ways to engage customers, streamline operations and build data-driven product models. But according to MIT NANDA’s State of AI in Business 2025 Report, 95% of organizations report no measurable business return from their AI initiatives. The report points to a lack of contextual learning and brittle workflows as key reasons these projects fail. Many tools simply aren’t connected to the right data, or integrated deeply enough into enterprise workflows to generate meaningful results. 

This blog explores how Capital One Software’s Databolt, built to integrate seamlessly with Snowflake, helps enterprises address this challenge by enabling secure, governed access to data that drives innovation.

Data protection isn’t about restriction; it’s about enabling smarter, safer business outcomes. However, risk concerns often leave sensitive data siloed in isolated systems, governed by strict access controls or manually de-identified in ways that break downstream analytics. This creates friction across the enterprise:

• Slower innovation cycles: Teams often spend weeks waiting for access to the data they need–and sometimes never get it at all. Instead of bringing valuable insights to the business quickly, they get stuck obtaining permissions, extracting, transforming and validating fragmented datasets that are missing key fields or context. 

• Reduced model accuracy: When data is stripped or masked excessively, models train on biased or incomplete distributions. That can lead to outcomes like false negatives in fraud detection or mis-personalized customer interactions. 

• Data trust erodes: When teams work with redacted or incomplete datasets, they lose confidence in the insights they deliver. Executives might hesitate to act on AI-driven recommendations because they know the underlying data is only partially representative, slowing adoption of new solutions. 

• Missed opportunities: Every day a business underleverages one of its most strategic assets is a day it misses valuable product and customer insights. Over time, this gap can grow, leaving enterprises trailing competitors who have unlocked data safely and put it to work.

The challenge for today’s executives shouldn’t be choosing between security and innovation. It’s finding a way to make them work together. How do you unlock the full value of sensitive data while keeping it governed, protected and available at the speed your business needs?

At Capital One, data is in our DNA. More than a decade ago, Capital One began a transformation to reinvent our technology operating model to enable the agility and innovation we needed to set the pace in the market. We moved fully to the public cloud, modernized our infrastructure and adopted open source technologies. As our cloud environment matured, we recognized the need for a solution that could protect sensitive data while still making it available to the systems and people who relied on it. 

The approach that met those requirements was tokenization. Unlike encryption or masking, tokenization is purpose-built for scenarios where data needs to stay usable (see our Beyond Encryption white paper). Encryption secures data but often requires decryption before use which introduces risk and latency. Masking obscures data for non-privileged users but can destroy relationships between data elements, making it less valuable for analytics or AI training. 

Tokenization solves these challenges by replacing sensitive data with format-preserving tokens, allowing systems to operate as if they were using the real data but without exposing the underlying values. This keeps sensitive data secure at the source while preserving the relationships needed for analytics and AI, reducing audit scope and simplifying governance. 

When we could not find a solution with the performance, flexibility and scale our business required, we built our own. That internal solution served as the inspiration for Databolt, our commercial-grade data tokenization offering.

Databolt was built to help companies protect their most sensitive data. We partnered with Snowflake to make it even easier for enterprises to unlock that data safely, preserve the context AI models need to deliver accurate, reliable results and integrate those protections seamlessly into existing infrastructure. 

Databolt is the first tokenization solution to natively integrate with Snowflake through Snowpark Container Services (SPCS), enabling tokenization to run directly within a customer’s Snowflake environment. This architecture delivers four key advantages for enterprises modernizing their data security strategy:

• Simplified governance: Databolt aligns with existing Snowflake roles and permissions, streamlining access governance and avoiding the need for new policies or manual reconfiguration. 

• Enhanced security: Sensitive data never leaves Snowflake’s trust boundaries, meaning all tokenization operations happen inside Snowflake’s environment, reducing exposure risk and simplifying governance. 

• Scalability with minimal overhead: Snowflake’s fully managed compute scales automatically to meet workload demand, allowing Databolt to deliver performance at enterprise-scale without adding operational complexity. 

• Ease of deployment: Databolt can be installed from the Snowflake marketplace and configured in about 30 minutes with minimal technical effort.

By combining strong governance with seamless scalability, Databolt and Snowflake transform data protection from a guardrail to a growth enabler. Organizations can accelerate AI initiatives, make better decisions and innovate faster—all while keeping sensitive data secure at rest, in motion and in use.  

Watch the on-demand webinar, Capital One Software and Snowflake: Partnering for secure data innovation with Databolt, to see these capabilities in action.

Ready to explore how Databolt can modernize your data security strategy? Contact us for a demo.