Interactive Agent Dynamic Feed for Personalized CRM Data Views
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Solution Overview
Problem
Traditional CRM systems require users to interact through structured interfaces with static feed patterns, which are inefficient, cumbersome, and error-prone, preventing natural language interaction while ensuring data security and accuracy.
Innovation Solution
An interactive agent utilizing a dynamic feed pattern that personalizes and adapts information based on user interactions, preferences, and real-time data changes, employing deep learning models to provide context-aware content through a dynamic user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional structured interfaces with static feed patterns are used, then data security and accuracy are maintained, but user interaction efficiency and natural language capability deteriorate
Solution Approach 1:
The patent implements a dynamic feed pattern that automatically adapts the user interface structure based on real-time user interactions and data context. The interface transitions from static to dynamic, where feed patterns are generated on-demand based on user behavior, data types, and interaction history, enabling natural language queries while maintaining security and accuracy through automated interface generation
Solution Approach 2:
The system performs self-service by automatically generating and adapting interface structures without requiring manual configuration. The feed pattern generation is autonomous, using machine learning models to infer user needs and create appropriate interfaces automatically, reducing the burden on users while maintaining system complexity management
2Adaptability or versatility
If static feed patterns are used, then interface consistency is maintained, but adaptability to user preferences and real-time data changes deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where user interactions with the interface are continuously monitored and used to refine future feed pattern generations. The system learns from user behavior patterns and adjusts interface structures accordingly, maintaining data accuracy while improving adaptability to individual user preferences through continuous feedback loops
Solution Approach 2:
The system dynamically changes interface parameters such as display format, data organization, and interaction modes based on real-time data changes and user preferences. The feed patterns adapt parameters like sorting, filtering, and presentation based on current context while maintaining core data integrity and accuracy through controlled parameter transformations
3Productivity
If structured interfaces are used, then data security is maintained, but interaction time and efficiency deteriorate
Solution Approach 1:
The patent performs preliminary actions by pre-generating and caching feed patterns based on common user queries and data structures. The system proactively prepares interface configurations before users make requests, using predictive models to anticipate needs and reduce interaction time while maintaining security through pre-validated interface structures
Solution Approach 2:
The system replaces manual mechanical interface navigation with automated AI-driven interface generation. Instead of users manually configuring interfaces, the system uses machine learning models to automatically generate appropriate feed patterns, substituting mechanical interaction steps with intelligent automation and reducing overall interaction time
Data Source
AI summary
An interactive agent may utilize a dynamic feed of a user interface to output an indication of a first data object in a first format based on a natural language request from a user device for the first data object. Based on an indication that the request for the first data object is associated with a user profile and an interaction with the indication of the first data object, modification data that indicates a modification for the first format may be mapped to the user profile. The interactive agent may modify a second format for an indication of a second data object to match the modification of the first format for the first data object based on the modification data and a natural language request for the second data object. The dynamic feed may output an indication of the second data object in the modified second format.