When the founders at Phasis Inc. sought to develop a platform for orienting AI agents, they turned to graphs as a way to obtain a measurement of culture.
The company wanted to better understand relations not just between people, but between a person and their values, beliefs and subcultures. The goal was to map culture in ways that agents could comprehend what culture was composed of and make decisions based on its fast-changing nature.
“The realization after the success we had with culture was that the same process that we had to apply in terms of cleaning, in terms of verification, in terms of creating ontologies, would map really well to other domains,” said Brandon Farley (pictured), co-founder and chief executive officer of Phasis. “That’s what Phasis is, it’s that same representation of reality and the real world and what we call the World API that represents many different domains for agents to orient against. Reasoning has scaled incredibly, and every week it is advancing further and further, but expertise and understanding of the world is not as fast. That’s where we see ourselves.”
Farley spoke with John Furrier for theCUBE + NYSE Wired: AI Luminaries interview series on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Phasis is building an orientation framework for agents in the enterprise. (* Disclosure below.)
Worlds for orienting AI agents
The Phasis World API is designed for production agents. A World is the maintained, evidence-backed state of the domain, and the company builds and deploys Worlds so agents can be oriented before work begins and stay current as circumstances change.
“The World API is really designed to be built into the systems as they are now, and the primitives that are required to build this kind of reality layer and expertise,” Farley explained. “The compounding that happens now with agents that are oriented against reality is going to set apart the companies that are catching up in the future and whose agents are kind of piecing it together every single time. The durable asset is the World model, and we feel like the companies that are able to use it are going to be pretty quickly far ahead.”
The primary endpoint for Phasis is called “/orient.” Users can send a task to “/orient” and Phasis will return the relevant World frames an agent needs to start, encompassing current state, material changes, supporting evidence, and uncertainties.
“It’s really about adding that orientation step before an agent goes out and searches or plans or strategizes,” Farley told theCUBE. “It’s a quick check against reality across the shared world or your private world as well. That one endpoint is made to give that orientation to any agent before they start, to know where to look, to know what they don’t know.”
Phasis’ tagline is “Models Reason. Worlds Orient.” and the company has positioned itself as a resource for agentic deployment. It is part of an AI future that is expanding quickly, and there are more advances yet to come, according to the Phasis CEO.
“We’re seeing smaller models that are incredibly capable,” Farley said. “What I feel we’re going to witness over the next year is that scaling up of these agent swarms and auto research. All of the ways that we’ll be able to apply this intelligence will be remarkable. We’re going to see some really great things come to the surface that have never been possible before.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of theCUBE + NYSE Wired: AI Luminaries interview series:
(* Disclosure: TheCUBE is a paid media partner for theCUBE + NYSE Wired: AI Luminaries interview series. Neither Neo4j, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)