C3.ai, inc. (20240202221). GENERATIVE ARTIFICIAL INTELLIGENCE ENTERPRISE SEARCH simplified abstract
Contents
GENERATIVE ARTIFICIAL INTELLIGENCE ENTERPRISE SEARCH
Organization Name
Inventor(s)
Thomas M. Siebel of Woodside CA (US)
Nikhil Krishnan of Los Altos CA (US)
Michael Haines of San Mateo CA (US)
Romain Juban of San Francisco CA (US)
GENERATIVE ARTIFICIAL INTELLIGENCE ENTERPRISE SEARCH - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202221 titled 'GENERATIVE ARTIFICIAL INTELLIGENCE ENTERPRISE SEARCH
The patent application describes systems and methods that use data models from multiple data domains within an enterprise information environment to generate potential responses to a prompt, with access controls in place.
- The systems select a deterministic response based on scoring validation data and access controls, ensuring privacy and security.
- These enterprise generative AI systems provide traceable references to the source information, enhancing transparency.
- Users benefit from increased utility in accessing information, analyses, and predictive analytics from both internal and external systems.
- Potential Applications:
This technology can be applied in various industries such as finance, healthcare, and e-commerce for personalized responses and insights.
- Problems Solved:
The technology addresses the need for granular access controls, privacy protection, and secure data handling in enterprise environments.
- Benefits:
- Enhanced privacy and security measures - Improved transparency and traceability of AI-generated insights - Increased utility and accessibility of information for enterprise users
- Commercial Applications:
Title: Enhanced Enterprise Data Security and Insights Generation This technology can be utilized by large corporations, government agencies, and organizations with sensitive data to ensure secure and efficient data processing.
- Prior Art:
Researchers can explore existing patents related to AI-generated responses, data security, and privacy protection in enterprise environments.
- Frequently Updated Research:
Stay updated on advancements in AI data modeling, privacy regulations, and security measures in enterprise information environments.
- Questions about Enterprise Generative AI:
1. How does this technology ensure data privacy and security in enterprise environments? 2. What are the potential implications of using this technology in industries like finance and healthcare?
Original Abstract Submitted
systems and methods are configured to generate a set of potential responses to a prompt using one or more data models with data from at least a plurality of data domains of an enterprise information environment that includes access controls. a deterministic response is selected from the set of potential responses based on scoring of the validation data and restricting based on access controls in view profile information associated with the prompt. these enterprise generative ai systems and methods support granular enterprise access controls, privacy, and security requirements. enterprise generative ai providing traceable references and links to source information underlying the generative ai insights. these systems and methods enable dramatically increased utility for enterprise users to information, analyses, and predictive analytics associated with and derived from a combination of enterprise and external information systems.
