Systems | Development | Analytics | API | Testing

Today, we are excited to announce the general availability of Claude 3.5 Sonnet as the first Anthropic foundation model available in Snowflake Cortex AI. Customers can now access the most intelligent model in the Claude model family from Anthropic using familiar SQL, Python and REST API interfaces, within the Snowflake security perimeter.

Though AI is (still) the hottest technology topic, it’s not the overriding issue for enterprise security in 2025. Advanced AI will open up new attack vectors and also deliver new tools for protecting an organization’s data. But the underlying challenge is the sheer quantity of data that overworked cybersecurity teams face as they try to answer basic questions such as, “Are we under attack?”

Marketers at financial services companies have their work cut out for them. Their companies have a wealth of data, but that data is often fragmented among different systems and divisions, and protected-class data has a wide range of restrictions on how it can be used for different product lines.

As organizations mature in their execution of data and AI initiatives, a burning question remains: How do we measure the effectiveness of our teams and our impact on the business? This isn’t the perennial “What’s my data worth?” dilemma often asked rhetorically and answered theoretically. Today’s challenge is concrete: to define and track the metrics used to justify continued investment in data and AI innovation.

We often hear from customers that they’re excited about what they could do with data and AI but are not sure how to do it. Or that the tech teams are “all in” but they can’t convince the powers that be to move forward. It’s not that they don’t know what to do — they could list a number of initiatives or use cases that would benefit from insights from their data or to which they could apply AI. But many organizations seem to suffer from institutional paralysis.

We had a busy week catching up with customers and partners at Microsoft Ignite in Chicago and online. We shared lots of exciting innovations to help customers build applications, keep their data architecture open and flexible and harness the power of AI in so many ways. Here’s a quick recap.

For years, companies have operated under the prevailing notion that AI is reserved only for the corporate giants — the ones with the resources to make it work for them. But as technology speeds forward, organizations of all sizes are realizing that generative AI isn’t just aspirational; it’s accessible and applicable now.

A revolution is underway as martech and adtech continue to converge around first-party data — and the revolution is happening on Snowflake. This seismic shift isn't a mere trend; it’s a game-changing transformation that will continue to shape the way that marketers and advertisers connect with consumers amid increasing privacy regulations, new identity frameworks and rising customer expectations.