Dynamic Orchestration Workflow for Conversational Bots
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Solution Overview
Problem
Manual design of conversational bots is time-consuming, requires intensive computation, and results in limited scope, necessitating a more efficient method for orchestrating digital conversational systems.
Innovation Solution
A system that generates a contextual execution dependency graph from stateful declarative automation task definitions, runtime execution logs, and supervised repairs to produce agents and calculate an agent sequence for executing automation scripts, enabling dynamic orchestration of stateful automation tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual design methods are used for conversational bots, then developers can create custom automation scripts, but the process becomes time-consuming and computationally intensive
Solution Approach 1:
The system enables self-service automation by allowing the conversational bot to automatically generate and execute automation scripts based on user intent, eliminating the need for manual developer intervention for each automation task. The bot autonomously creates customized automation workflows by interpreting natural language requests and translating them into executable scripts.
Solution Approach 2:
The patent replaces the mechanical manual design process with an automated computational system. Instead of developers manually creating automation scripts, the system uses natural language processing and automated script generation technologies to substitute the manual mechanical process with an automated digital workflow that interprets user intent and generates scripts automatically.
2Adaptability or versatility
If manual design of conversational bots is performed, then custom automation can be achieved, but intensive computation and human monitoring are required
Solution Approach 1:
The system extracts the complex computation and monitoring functions from the manual design process and consolidates them into automated background processes. The computationally intensive tasks of script generation, validation, and execution monitoring are automatically handled by the system infrastructure, removing the burden of human monitoring while maintaining high automation scope.
Solution Approach 2:
The patent implements a universal automation framework that handles multiple functions through a single integrated system. The same system infrastructure that generates automation scripts also monitors their execution, manages resources, and handles various types of automation tasks, reducing overall system complexity despite the broad automation scope.
3Productivity
If existing automation scripts are manually executed, then automation tasks can be performed, but the process lacks efficiency and scalability
Solution Approach 1:
The system performs preliminary action by pre-generating and caching automation scripts based on anticipated user needs and common automation patterns. When users request automation, the system can quickly retrieve and execute pre-prepared scripts or make minimal modifications to existing templates, significantly reducing execution time compared to manual script creation and execution.
Data Source
AI summary
A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include receiving data and generating a contextual execution dependency graph with said data. The operations may include producing agents with said data and calculating an agent sequence for said agents based at least in part on said contextual execution dependency graph. The operations may include executing an automation script using said agent sequence and said contextual execution dependency graph.