Unknown Organization (20240256598). GENERATIVE AI AND AGENTIC AI SYSTEMS AND METHODS FOR PRODUCT DATA ANALYTICS AND OPTIMIZATION simplified abstract
Contents
GENERATIVE AI AND AGENTIC AI SYSTEMS AND METHODS FOR PRODUCT DATA ANALYTICS AND OPTIMIZATION
Organization Name
Inventor(s)
Brian Mccarson of Chandler AZ (US)
GENERATIVE AI AND AGENTIC AI SYSTEMS AND METHODS FOR PRODUCT DATA ANALYTICS AND OPTIMIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240256598 titled 'GENERATIVE AI AND AGENTIC AI SYSTEMS AND METHODS FOR PRODUCT DATA ANALYTICS AND OPTIMIZATION
The abstract of the patent application describes the development of generative AI systems and methods for providing recommendations related to various aspects of product analytics, such as sales, pricing, inventory, orders, manufacturing, distribution, shipping, and packaging, based on available data sources. A consistent semantic metadata structure is outlined, along with a hypothesis generating and testing system capable of creating predictive analytics models in a non-supervised or partially supervised mode. Users or AI agents can subscribe to the data for use in economic forecasting.
- Semantic metadata structure for product analytics
- Hypothesis generating and testing system for predictive analytics models
- Non-supervised or partially supervised mode for AI systems
- Subscription model for users and AI agents for economic forecasting
- Utilization of a range of available data sources for recommendations
Potential Applications: - E-commerce platforms - Supply chain management - Retail industry - Financial forecasting - Market research
Problems Solved: - Efficient product sales strategies - Optimal pricing decisions - Inventory management optimization - Streamlined manufacturing processes - Enhanced distribution and shipping logistics
Benefits: - Improved decision-making processes - Increased efficiency and productivity - Enhanced competitiveness in the market - Better customer satisfaction - Cost savings and revenue growth
Commercial Applications: Title: AI-driven Product Analytics for Enhanced Decision-making in E-commerce This technology can be utilized by e-commerce platforms to optimize product sales, pricing, inventory management, and other aspects of the business, leading to improved profitability and customer satisfaction. Market implications include increased competitiveness and market share for businesses implementing this technology.
Questions about AI-driven Product Analytics: 1. How does the semantic metadata structure enhance the efficiency of product analytics? The semantic metadata structure ensures a consistent and organized approach to data analysis, leading to more accurate and reliable recommendations for businesses. 2. What are the key benefits of using a hypothesis generating and testing system in predictive analytics models? The hypothesis generating and testing system allows for the creation of more robust and accurate predictive models, improving the quality of recommendations provided to users.
Original Abstract Submitted
generative ai systems and methods are developed to provide recommendations regarding product sales, pricing, inventory, orders, manufacturing, distribution, shipping, packaging or other product analytics as determined from a range of available data sources. a consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. users and/or ai agents (i.e., a form “agentic ai”) may then subscribe to the date for the use in economic forecasting.
