Agentic AI has been heralded as the next innovation frontier for the future of work. For enterprises to succeed in implementing agents across operations, however, three imperatives must be met: Defining and codifying ROI, building trust in outcomes, and enabling seamless collaboration between humans and AI agents.

These imperatives all fall into Sema4.ai Inc.’s SAFE framework, which demands that enterprise-grade AI be secure, accurate, fast and extensible. SAFE is poised to reach more enterprise users, with the Team Edition of the company’s Enterprise AI agent platform now part of the Snowflake Marketplace.

“It’s a big milestone for us,” said Paul Codding (pictured, left), co-founder of Sema4.ai. “It enables customers to quickly be able to build, deploy and manage agents directly within their Snowflake environment. We’re connecting their Snowflake data and our ability to connect closely with our Cortex AI to be able to help them go from data to insights to action.”

Codding and Tommi Holmgren (right), vice president of product at Sema4.ai, spoke with theCUBE’s Scott Hebner at the AI Agent Builder Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed Sema4.ai laying the foundation for trust and ROI realization in implementing enterprise AI agents. (* Disclosure below.)

Team Edition makes AI agents ‘SAFE’

With deeper integration into Snowflake Cortex and Snowpark Container Services, Team Edition unlocks secure, accurate, fast and extensible agent deployments, fulfilling the four design principles that underpin Sema4’s platform. Beyond the product element, this integration combines intensified industry partnerships with surging enterprise adoption and Sema4’s mission to become the horizontal foundation for AI-powered work across industries.

“What excites us is how these successes are helping us attract larger companies, like ISVs, that are looking at building their agent solutions on top of our platform, Snowflake included,” Codding said. “We’re excited about the momentum, the additional funding and the work that we’ve done with Team Edition.”

In a departure from conventional AI architecture, Sema4.ai champions a “zero-copy” data model: Instead of moving data to the AI, they bring the AI to the data. This inverts traditional data processing logic, enhancing security, reducing latency and maintaining compliance — all while keeping sensitive enterprise data within Snowflake’s controlled environment.

“I think the zero-copy data access comes to life with our Snowflake-deployed agents,” Holmgren said. “Previously, it meant that we didn’t copy the data over to the agent, but now we bring the agent all the way to where your data lives. Within your Snowflake security envelope, you have your data, and you also run your agents. So, agents come to your data. All of those services that you’ve deployed in your Snowflake account are available for the agents within the same security perimeter.”

Perhaps the most transformative feature of Sema4.ai’s approach is its democratization of agent building. With natural language-based run books and an intelligent assistant named Sai, non-technical users can design, refine and deploy AI agents without writing code.

“At the end of the day, these agents need to be able to perform work,” Codding said. “The people doing that work are predominantly non-technical people. These are not Python experts or AI experts. Our natural language run books make it easy to quickly get what’s in your head, what you want the agent to do, onto paper to be able to enable it to quickly perform that work.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the AI Agent Builder Summit:

(* Disclosure: Sema4.ai Inc. sponsored this segment of theCUBE. Neither Sema4 nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE