AI Search Agent for Dynamic Knowledge Base Curation
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Solution Overview
Problem
Traditional search tools face limitations such as limited information delivery, absence of content curation, restricted access and interaction, over-reliance on specific keywords, lack of integration and personalization, and the absence of a knowledge base to store and reuse information.
Innovation Solution
The development of an intelligent search agent using AI and ML capabilities to create a specialized searchable knowledge base that is automatically updated and expanded based on search activity, providing curated and contextually relevant information, and allowing for interactions beyond traditional search limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional search engines are used to retrieve information, then accessibility to vast amounts of information is improved, but information quality and relevance deteriorate due to lack of curation
Solution Approach 1:
The patent introduces an AI-powered intermediary system that sits between the user and the vast information landscape. This intermediary automatically curates, filters, and organizes information from multiple sources, delivering only relevant and high-quality content to users. The AI agent acts as a mediator that transforms the overwhelming quantity of available information into curated, actionable insights, resolving the contradiction between information accessibility and information quality.
2Quantity of substance
If traditional search tools provide extensive search results, then information coverage is improved, but user time and effort to process results worsen
Solution Approach 1:
The patent implements a self-service information retrieval system where the AI-powered search agent autonomously performs information gathering, filtering, synthesis, and delivery without requiring user intervention. The system automatically manages the entire search process including querying multiple sources, evaluating result quality, organizing information, and presenting curated outcomes. This eliminates the need for users to manually process extensive search results, resolving the contradiction between comprehensive information coverage and user time investment.
3Measurement precision
If AI methods are used to analyze and index data according to multi-dimensional vectors, then search precision is improved, but system complexity worsens
Solution Approach 1:
The patent extracts the complex AI-powered vector analysis and multi-dimensional indexing operations into a separate, specialized AI processing layer. This extracted AI module handles the computationally intensive tasks of semantic understanding, vector representation, and similarity matching, while the main system architecture remains relatively simple and focused on orchestrating the AI agent and managing information flow. By separating the complex AI functionality from the core system, the patent achieves high search precision while managing system complexity through modular design.
Data Source
AI summary
An intelligent search agent that can accept search request input in various ways to initiate a search of databases, websites, documents, PDF files, photos, and other digital data. Search requests can be initiated manually, through automated scheduling, and other ways and can be initiated in multiple ways including voice input, text input, form filling, large language model (LLM) processes, AI agents, selecting from dashboard menus, computer instructions and other methods. Applications of machine learning (ML) and natural language processing (NLP) and others are used to enhance the search agent's capabilities while minimizing user effort requirements. The Search Agent works in conjunction with a knowledge base function to dynamically form and manage one or more knowledge bases using search results and to automatically integrate search results into workflow processes.