RPA and Chatbots: A Powerful Intersection of AI and Robotic Process Automation


Humans are entering a new era - the automation era, where humans and machines will increasingly work side by side. Some of you might already be aware of the popularity of Chatbots and RPA in the hyper automation ecosystem for enterprises. However, the bigger question is, what would happen if we integrate these two robust technologies? Would we get more advanced and powerful capabilities once we combine them?

From the recent past, an advanced edge over Artificial Intelligence(AI) has created a new wave of opportunities that are expected to disrupt enterprise automation. Hence, the expectation with Automation has exponentially raised with time. The expectation now with Automation has evolved from being a simple rule-based model to a cognitive model that displays higher intelligence in the journeys that a process is expected to take.

In this article, we will explore how these two robust technologies, when combined together, disrupt the organization’s approach towards business process automation and how Yellow Messenger is helping enterprises solve their challenging problems by eliminating rule-based models and introducing cognitive models.

What Is RPA ?

To put it in simpler terms, Robotic Process Automation(RPA) is the process of automating business operations with the help of robots to reduce human intervention.

RPA uses software robots to automate repetitive tasks and manual processes—enhancing the work of your employees by interacting with websites, business and desktop applications, databases, and people to execute repetitive and often mundane work. RPA is often used to automate and streamline back-office operations in Banking, HR, Finance, etc.

RPA and Chatbot Integration

In a generic scenario, a chatbot interacts with a user, identifies their intent, and helps them complete the intended user journey. From a use-case perspective, a chatbot often integrates with systems like CRM, HRMS, etc. to fetch and store relevant information of the user. Often, these systems might not support APIs, which is generally used by a chatbot to integrate.

RPA plays a critical role in such a scenario where it can seamlessly integrate with our chatbots and help the chatbot to complete a business process, access, or store information with legacy systems that do not have APIs.

We have integrated with RPA providers like UiPath, Automation Anywhere, etc seamlessly through APIs and other means as per the use-case. Taking an example of our integration with UiPath, we consume their Orchestrator’s RESTful API’s to interact with our chatbot. As and when required, our chatbot gathers relevant user data, filters it in our platform through cloud functions for complex journeys and pushes the data in queue or as queue items through relevant API calls. When the RPA process is completed, an API call is being made to our message API, whose payload contains data that needs to be processed in our platform or it needs to be reflected in the chatbot. In either of the cases, relevant data is posted to our chatbot within the same session for any unique user, thereby enabling bi-directional flow of data.

The bi-directional flow of data between our chatbot and RPA allows our chatbot to orchestrate with RPA bots and processes. Enterprises get hard time-retaining their user’s when the RPA process is processed and ultimately users drop off which leads to increase in resolution time leading to bad user experience. With our intelligent chatbots and seamless bi-directional integration, enterprises need not worry about user drop off, slower resolution time and bad user experience.

“By 2022, 65% of organizations that deployed robotic process automation will introduce artificial intelligence, including machine learning and natural language processing algorithms”

Yellow Messenger’s pre-built integration with tools like CRM, ERP, HCM, etc allows enterprises to quickly set up their flow without any additional efforts. Various scenarios demand many child chatbots to work with only one main chatbot, this is where our Bot orchestrator (not the RPA orchestrator) plays a major role which uses a recommendation engine to suggest the most relevant responses and orchestrates among the most relevant bot in over 100+ languages across channels like WhatsApp, Google Business Messages, FB Messenger, etc.

RPA requires a procedural training of the process, i.e, it would require to be hand holded at various instances whereas our chatbot works on semantic model for querying, which can be easily trained with words. With powerful Machine learning and NLP models, our chatbot’s self-learning capabilities and conversational insights are extensively helpful for enterprises to understand the end-user and their needs over time.

Our intelligent chatbots act as a front-facing layer that gathers, filters, and processes the user data while engaging with the user and running the RPA process in the back office.

How Chatbots and RPA Compliments Each Other?

How Chatbots and RPA Compliment each other

RPA can provide quick relief as a noninvasive form of integration. However, business processes are not always rule-based and repetitive. Business processes often require cognitive decision-making capability with optimization and a single tool like RPA cannot find scalable solutions alone. Yellow Messenger bots, designed in a cognitive engagement cloud give an edge to your bot to achieve end-to-end automation. A couple of ways through which Chatbot and RPA compliments are:

1. Processes & Inputs: RPA works well when the process is rule-based, repeatable, and predictable for structured data, whereas, our chatbot can work well for unstructured conversations for any specific use-case to trigger an RPA process. 2. Intelligence Layer: Our chatbot, designed in a robust cognitive engagement cloud, intelligently identifies user intent, gathers data around it, and structures it as per the need of the RPA process. Our chatbot’s self-learning capability helps the automation process to make more intelligent decisions over time to streamline the business flow. 3. Real-time Execution: An RPA, integrated with a chatbot can handle complex and real-time queries from users at scale. Our chatbot helps the RPA process to gather real-time data from the user to process it and give relevant information back by enabling 2-way communication. 4. User Experience: Traditional ways of gathering user data to run RPA bots, e.g, Surveys, Forms, etc. have drastically reduced user engagement as these forms of engagement require a waiting period for the users to get feedback. Having an intelligent chatbot deployed to make things convenient for users, gets a higher user engagement and better experience. Chatbot, being a front-facing layer, understands the intent of the user and simulates a human-like conversation, whereas the RPA bot echoes the activity of a human in back-office. Ultimately, the chatbot understands the customer’s intent and RPA works behind the scenes to make it happen.

When and where can Chatbot and RPA work together?

Think of it in this way, whenever and wherever you feel that a highly administrative, repetitive, rule-based and predictable task needs to be done in a legacy system by a human, an RPA can fit in to take over this mundane task. Generally, the human working on the mundane task would need some data to execute a business process in RPA, and if he/she is getting that data from an internal or external user, adding a chat or voice-based bot makes sense.

But wait! Would just adding a conversational channel suffice in achieving end-to-end automation? Well, that’s a straight no!

With RPA, enterprises can streamline a part of their automation, but to scale beyond this initial plain sailing process, business leaders are taking a step further with us. Data is the new oil, and we kid you not when we say this; that we help leaders capture meaningful data which creates an actual impact on the business. Meaningful data that you had been losing all up until now. As a business, you have some information that needs to go through a repetitive process and you use RPA and get the output; now imagine having a digital conversational interface that can capture user’s sentiment, intent, engagement frequency, and a lot more, with enabling the same RPA process that too with a fraction of the time taken earlier! The more you dig with us, the more data will be captured by our bot.

Common use-cases of AI and NLP working together with RPA are not limited to but includes various industry and domain-specific scenarios like:

- Insurance Claims (involves capturing user data, processing claims, etc.)

- Customer Service with 24/7 support (instant resolution)

- HR Virtual Assistant (Resume filtering using OCR, Remote onboarding, etc.)

What is the outcome of this integration?

The combination of Chatbot and RPA can solve some of the major challenges for an enterprise. It helps enterprises overcome rising internal and external support expectations with reduced operational costs by solving user queries without any human intervention. This also helps an agent to become more efficient, as they will not have to invest their time and energy in mundane tasks like fetching user information from a Database and storing relevant data back.

A super-intelligent design of this integration will not only help users to get their queries resolved faster but will also give the organization an edge over its competitors by having an exceptional digital branding.

More and more enterprise leaders are delivering end-to-end automation beyond RPA by collaborating with our conversation-based AI technologies to augment business processes and we can help your organization too!

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Shubham is working in the Product Team at Yellow Messenger, enabling various enterprise and product-level integrations. He enjoys intersecting technology with empathy to deliver solutions that the end-user would simply fall in love with.

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