Florida Patent of the Month – April 2025

Curio XR has secured U.S. Patent No. 12,265,788, titled “Systems and methods for connected natural language models,” introducing a novel approach to AI collaboration that balances data privacy with performance. The system enables multiple large language models (LLMs) to work together across isolated datasets, allowing organizations to harness AI insights without compromising sensitive information.

A Modular AI Network for Sensitive Environments

The patented system allows a local LLM—such as one operating within a school, hospital, or enterprise—to identify and query external LLMs that have access to different private datasets. The local model sends a user query to the appropriate external model, receives the answer, and then generates a final response for the user. Crucially, the external models never access the local data, and vice versa, preserving strict data boundaries.

This architecture is particularly relevant for sectors like education, healthcare, and finance, where data privacy regulations are stringent. It enables AI systems to collaborate without violating compliance requirements.

Real-World Impact: From Classrooms to Clinics

Curio XR, known for its immersive educational tools, is expanding its reach with this patent. The technology could support applications ranging from virtual science labs that integrate real-time research data to healthcare assistants that draw on specialized medical knowledge—all while keeping user data secure.

As AI adoption accelerates, Curio XR’s innovation offers a scalable, privacy-conscious framework for cross-model intelligence.

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