Unified Virtual Assistant for Enterprise Stakeholders
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Solution Overview
Problem
Existing virtual assistants lack personalized, human-like experiences across various stakeholders in an enterprise, fail to perform low-complexity tasks, and require multiple bots for different processes.
Innovation Solution
A generative artificial intelligence-based unified virtual assistant that receives multi-modal queries, creates user contexts, generates optimized prompts, and provides responses using a large language model and customized tool array, offering a single conversational system for various tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate virtual assistants are used for different enterprise processes, then each assistant can be specialized for its specific domain, but the system complexity increases and requires multiple bots for various tasks
Solution Approach 1:
The patent merges multiple domain-specific virtual assistants into a single unified virtual assistant that handles IT service desk, employee self-service, human resource, and other enterprise processes through one system, reducing the number of separate bots while maintaining domain expertise through specialized modules
Solution Approach 2:
The unified virtual assistant is designed with multi-functionality to perform diverse enterprise tasks across different domains including IT service management, human resources, employee self-service, and supply chain operations, allowing a single system to replace multiple specialized assistants
2Device complexity
If conventional rule-based virtual assistants are used, then the system is simple to implement, but they cannot provide personalized, human-like experiences or perform low-complexity tasks
Solution Approach 1:
The patent transitions from rule-based parameters to generative AI parameters that enable natural language understanding, contextual awareness, and personalized responses, allowing the virtual assistant to adapt to different users and tasks while maintaining ease of deployment through cloud-based infrastructure
3Measurement precision
If contextual virtual assistants use extensive databases for accurate answers, then query accuracy improves, but the system requires extensive data access and increased complexity
Solution Approach 1:
The patent introduces an enterprise knowledge graph as an intermediary layer between the virtual assistant and extensive databases, enabling accurate query responses through structured knowledge representation without requiring direct access to complex database systems
Data Source
AI summary
This disclosure relates generally to a method and system for generative Al based unified virtual assistant. Conventional virtual assistant for enterprise systems needs to be configured for a specific industry or stakeholder and does not provide support for all stakeholders in the enterprise. Also, conventional rule-based virtual assistant or machine learning based virtual assistant need a large database for proper functioning. The disclosed method and system provide a unified virtual assistant for all processes in the enterprise. The unified virtual assistant provides support for all stakeholders in the enterprise and can answer all kinds of queries related to any process of the enterprise according to a role of a user logged into the system. The unified virtual assistant interprets user's query and generates effective prompts depending on the user's query which can be specific to customer, employee, executive or support desk users of the enterprise.