Whoop is building agentic AI maturity on a foundation of enterprise health data

Enterprise AI programs are moving beyond experimentation, but agentic AI maturity — the ability to run governed, autonomous workflows at production scale — remains out of reach for most organizations. The companies closing that gap fastest are the ones that invested early in clean data foundations.

Whoop Inc., the Boston-based health technology company known for its biometric wearable, is one of the clearest examples of this process in practice. The company’s journey from elite-athlete fitness tracker to full-scale health platform — now processing sensor data that captures heart rate, respiratory rate, heart rate variability, blood pressure and electrocardiogram readings — has made data infrastructure a first-order strategic priority, according to Matt Luizzi (pictured, right), vice president of analytics at Whoop.

“We’re capturing a ton of sensor data; this is data coming off the wrist that we’re processing, storing in our data lake,” Luizzi said. “Then, we want to use analytics to improve the product experience, understand how to get the product into the hands of more customers. Snowflake sits at the center of that. We power our entire business analytics function by Snowflake. And more recently, with AI, it’s really transformed the way that we’re able to accelerate our insight delivery and prove value to our members.”

Luizzi and Vivek Raghunathan (left), senior vice president of engineering and support at Snowflake Inc., spoke with theCUBE’s Dave Vellante and Rebecca Knight at Snowflake Summit 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Whoop is operationalizing AI workflows and advancing agentic AI maturity on Snowflake’s data platform, as well as interoperability strategies using Apache Iceberg and Polaris. (* Disclosure below.)

Agentic AI maturity and the tribal knowledge opportunity

The scale of Whoop’s data challenge is not trivial. The company currently holds more than three petabytes of data in its data lake, with 20 terabytes added per day, making interoperability and open standards such as Iceberg essential for long-term flexibility, Luizzi noted. That foundation has enabled Whoop to adopt Snowflake’s newest agentic tool — including Snowflake CoCo, the platform’s coding agent for enterprise data workflows — with what Luizzi described as immediate, measurable results.

“We’ve been putting a lot of effort into generating that clean semantic ontology over the past couple of years,” Luizzi said. “That’s really enabled us to take products like CoCo Desktop and immediately dive in and see value. What we’re seeing now is a shift in where humans are able to add value and where they’re needed to add value.”

Raghunathan framed the broader platform strategy around two complementary personas. He previously co-founded Neeva Inc., the AI search engine acquired by Snowflake, giving him an engineer’s perspective on where agentic tools are heading. Snowflake CoWork targets business users looking to extract insights from data, while Snowflake CoCo is built for developers and builders who construct the models, skills and intelligence those business users rely on. Both, he said, are present at every company.

“I think a lot of what we are seeing is [that we need to] start from first principles and ask what are the jobs to be done,” Raghunathan said. “Some of those activities will be activities where the input is well-defined and structured and the output is well-defined and structured. And if that’s the case, then an agent will do that activity. There’ll be a third class of activities — the input is fuzzy, the output is fuzzy — what I’d call fundamentally human activities.”

For Whoop, the practical effect of agentic AI maturity is already visible in how roles are evolving. The boundaries between what a product manager, analyst, designer and engineer do are blurring as agents absorb tribal knowledge and automate workflows that once required specialized expertise, Luizzi explained. The outcome, he said, is not fewer humans but more output.

“We’re starting to see some early signs that we’re really automating a lot of those more trivial workflows that just require tribal knowledge and manual work, and start to repurpose these same humans on these strategic value-add tasks for the business,” Luizzi said. “What we’re not seeing is the lack of need for humans. We’re seeing all this […] work kind of propagate, and we’re able to do a lot more things as a business, move faster, and ultimately deliver a lot more value to our customers.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit 2026:

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit event. Neither Snowflake, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE