Predictive Action Engine for Personalized Content Delivery
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Solution Overview
Problem
Organizations face challenges in effectively communicating and managing digital content within their systems, leading to missed updates and inefficiencies in information flow due to the proliferation of content and lack of targeted information delivery.
Innovation Solution
A predictive action engine monitors digital content sources, identifies relevant entities for users, and generates custom content items based on user interactions and machine learning models to improve information management and delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If employees manually manage the flow of digital content, then information can be communicated, but employees spend excessive time tracking and managing content
Solution Approach 1:
The system enables self-service by automatically generating custom content items and distributing relevant information to employees without manual intervention. The predictive action engine autonomously monitors digital content sources, identifies relevant entities, and delivers personalized content, allowing the information management system to serve itself rather than requiring employee management.
Solution Approach 2:
The patent replaces the mechanical manual management system with an automated machine learning-based system. The predictive action engine uses machine learning models to automatically process digital content, identify relevant entities, and generate custom content items, substituting human manual efforts with automated computational processes.
2Loss of information
If all digital content is shared organization-wide, then information availability increases, but relevant information is lost in the noise of excessive content
Solution Approach 1:
The system applies local quality by customizing content delivery for each employee based on their specific role, preferences, and interaction history. Instead of uniform content distribution, the predictive action engine generates personalized custom content items tailored to individual employee needs, making the information system adapt to local user characteristics.
Solution Approach 2:
The system implements feedback mechanisms by monitoring employee interactions with digital content and using this information to refine future content generation. The predictive action engine tracks how employees engage with generated content and adjusts its entity identification and content creation processes based on this feedback, continuously improving relevance.
3Loss of information
If employees are invited to all meetings where relevant information is shared, then information completeness improves, but meeting attendance becomes unmanageable
Solution Approach 1:
The system extracts only the essential information from meetings and other digital content sources, separating relevant content from the need for physical attendance. The predictive action engine identifies key entities and concepts from meeting transcripts and other sources, then generates custom content items that capture the essential information without requiring employees to attend meetings.
Solution Approach 2:
The predictive action engine acts as an intermediary between meeting content and employees. Instead of directly connecting employees to meetings, the system processes meeting content through entity identification and custom content generation, delivering filtered and personalized information to employees who need it.
4Measurement precision
If employees actively search for relevant content, then information accuracy improves, but time to find information increases
Solution Approach 1:
The system performs preliminary action by proactively generating and distributing custom content items before employees need to search for information. The predictive action engine continuously monitors digital content sources and pushes relevant information to employees in advance, eliminating the need for employees to actively search for content.
Solution Approach 2:
The information delivery system provides self-service by automatically identifying and delivering relevant content to employees based on their profiles and interaction patterns. Employees receive personalized content without needing to manually search or filter through organization-wide content.
Data Source
AI summary
A predictive action engine monitors digital content sources within an organization to detect generation or ingestion of digital content by computer systems of the organization. The engine determines one or more entities that are relevant to a user associated with the organization. The engine processes content items obtained from the digital content sources to detect an entity within a digital content item that corresponds to an entity of the one or more entities that are relevant to the user. The engine then generates a custom content item for the user based on the detected entity and at least a portion of the identified digital content item.