Intelligent IT Workflow Automation for Dynamic Data Volumes
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Solution Overview
Problem
Existing automation tools are limited to specific areas of IT automation, lacking a unified platform that can perform intelligent automation across the entire organization, and fail to efficiently handle dynamic and complex data volumes, leading to inefficiencies and imbalances in processing resources.
Innovation Solution
A system and method utilizing artificial intelligence and machine learning to automate workflow pipelines, enabling seamless execution of service requests across multiple environments, integrating data from various sources, and providing predictive insights for real-time actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional bot scripts are used for automation, then specific tasks can be automated, but they cannot handle dynamic and complex data volumes efficiently and lack versatility across different environments
Solution Approach 1:
The patent implements a universal automation platform that can handle multiple data protocols, communication paths, and computing platforms through a single system. The platform uses configurable bot scripts that can adapt to different environments and data volumes, eliminating the need for separate automation tools for each specific area.
Solution Approach 2:
The system dynamically adjusts to varying data volumes and complexity levels by using machine learning models that can process and adapt to changing data patterns in real-time, rather than relying on static bot scripts with fixed processing capabilities.
2Adaptability or versatility
If conventional automation tools are used for specific IT areas, then those specific tasks can be automated, but a unified automation platform across the entire organization cannot be achieved
Solution Approach 1:
The patent merges multiple specialized automation tools into a single unified automation platform that can handle cloud costs, cloud management, cybersecurity, AIOps, chatbots, and voice-related communication through one integrated system, reducing the number of separate tools needed.
Solution Approach 2:
The unified automation platform provides multi-functional capabilities across different IT domains through a common architecture, allowing the same platform to perform security orchestration, cloud management, and customer communication tasks without requiring separate specialized systems.
3Extent of automation
If bot scripts are configured to recognize target outcomes, then task automation can be achieved, but configuring them correctly is difficult and errors can occur
Solution Approach 1:
The system uses machine learning models that can automatically learn and adapt to target outcomes without requiring manual configuration of bot scripts. The automation system self-configures by analyzing data patterns and determining the appropriate actions, reducing the difficulty of setup and configuration.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors automation outcomes and uses machine learning to adjust and improve its decision-making, reducing configuration errors by learning from past performance rather than relying on static pre-configured rules.
4Ease of operation
If communication sessions are transferred to agents, then complex issues can be handled, but the sessions cannot be transferred back to bots when the agent completes the interaction
Solution Approach 1:
The patent implements continuous session management where communication sessions can seamlessly transition between bots and agents and back again. When an agent completes an interaction, the session can be transferred back to a bot for follow-up tasks, maintaining continuous automation rather than creating dead ends in the workflow.
Data Source
AI summary
The present subject matter discloses a system and a method for providing insights of an information technology ecosystem. The system comprises an ingestion module for ingesting at-least one data attribute from at least one data source into a data lake and a data analysis module for generating a dataset using data validation rules, wherein the data validation rules converts the at-least one data attribute to a predetermined format, and for generating at least one service request. Furthermore, the system comprises an automation module for determining a class of the at least one service request, wherein the class of at least one service request is determined based upon the dataset, wherein the class of at least one service request identifies a service provider from a plurality of service providers. Moreover, the automation module executes a pre-determined action based upon the class of the at least one service request and the identified service provider, wherein the pre-determined action provides a predictive insight in real-time.