RPA Bot Fulfillment Engine for Contact Center Automation
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Solution Overview
Problem
Contact centers face inefficiencies in automating repetitive, low-intelligence, frequently asked, or static processes, which can lead to resource misallocation and increased operational costs due to the need for human intervention in handling routine customer interactions.
Innovation Solution
Implementing Robotic Process Automation (RPA) bots integrated with various customer touchpoints, such as chatbots, emails, and IVR systems, that utilize intent recognition and a fulfillment engine to select and execute appropriate software bots for automating these processes through REST API requests, allowing for seamless interaction across different channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human agents handle all customer interactions, then service quality and flexibility are maintained, but operational costs increase and resource allocation becomes inefficient
Solution Approach 1:
The system segments customer interactions by analyzing intent and routing different types of interactions to different handlers (AI bots for routine tasks, human agents for complex issues). The fulfillment engine divides the automation process into discrete software bots that can be independently selected and executed based on interaction requirements.
Solution Approach 2:
The patent introduces an intent recognition module and fulfillment engine as intermediaries between customer interactions and the response generation system. These intermediaries analyze interaction intent, select appropriate software bots, and coordinate between multiple touchpoints, enabling intelligent automation without direct human intervention for routine tasks.
2Productivity
If AI bots are deployed to automate routine tasks, then operational costs decrease and productivity increases, but system complexity increases
Solution Approach 1:
The fulfillment engine serves as a universal platform that can select and execute multiple different software bots through a single interface. The system uses standardized REST API requests that can trigger various RPA bots, making the system scalable without proportionally increasing complexity. Multiple bots share common infrastructure for intent recognition, argument gathering, and result delivery.
Solution Approach 2:
The patent uses template-based approaches where software bots are created as reusable templates with standardized structures. The fulfillment engine uses metadata and argument templates to generate bot execution requests, allowing rapid deployment of automation capabilities without manually configuring each bot instance, thereby reducing system complexity.
3Adaptability or versatility
If multiple touchpoints are integrated with RPA bots, then customer service coverage improves, but integration complexity and maintenance burden increase
Solution Approach 1:
The fulfillment engine is designed as a universal platform that can trigger software bots from multiple different touchpoints (chatbots, emails, SMS, websites, IVR, mobile applications, agent workstations) through a standardized REST API interface. This allows the system to support multiple channels without creating separate integration paths for each touchpoint, reducing maintenance burden.
Solution Approach 2:
The patent extracts the complexity of bot selection and execution logic into a separate fulfillment engine component. This extraction allows the touchpoints themselves to remain relatively simple interfaces that only need to send REST API requests to the fulfillment engine, which handles the complex tasks of intent analysis, bot selection, and coordination.
4Measurement precision
If intent recognition and fulfillment engines are implemented, then automation accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-defining software bots, their metadata, and argument templates before runtime. The fulfillment engine has pre-established knowledge of available bots and their requirements, allowing it to quickly match interaction intent with appropriate bots without extensive real-time analysis or searching, thereby reducing processing time while maintaining accuracy.
Data Source
AI summary
A system and method are presented for creating bots for automating first party touchpoints with contact centers. Software bots created using Robotic Process Automation (RPA) are integrated with a contact center's different customer touch points (e.g. chatbots, emails and SMS, websites, IVR application, mobile applications, agent workstation). Artificial intelligence behind the touch points finds the intent of an interaction and the respective RPAs to be triggered using a fulfillment engine that finds and executes the appropriate fulfillment for each interaction intent. A REST API Request is sent to an RPA execution server, which runs the selected RPA and sends the result to the respective touch point that triggered it.