The platform functions by connecting established AI interfaces to the company's long-standing identity resolution engine. By operating entirely within a customer's virtual private cloud, the tool ensures that sensitive behavioral signals—including data from anonymous and pre-login users—never leave the organization's secure boundary. This approach addresses a common industry friction point where AI models are often hindered by fragmented, batch-processed, or incomplete datasets.
CEO Bill Bruno noted that the architecture is the culmination of 26 years of data-first development, designed to provide consistent, verifiable answers across various internal departments. Because the system is LLM-agnostic, enterprises maintain control over their governance and security protocols. This capability is aimed at sectors such as finance, healthcare, and insurance, where data privacy and auditability are critical requirements for adopting generative AI technologies.





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