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Unleashing the Power of Chatbots: Create Conversational AI Agents That Transform Customer Engagement

March 7, 2023

The increasing global prominence of artificial intelligence (AI) has led to an increased interest in chatbots and conversational AI. A chatbot is a computer program designed to simulate conversation with human users, typically through messaging applications, websites, or mobile apps. Conversational AI, on the other hand, refers to the use of Natural Language Processing (NLP) and other AI technologies to enable chatbots and other virtual agents to understand and respond to user inquiries in a human-like manner.  

It is important to note that while the terms "chatbot" and "conversational AI" are sometimes used interchangeably, they are not synonymous. A chatbot may utilize conversational AI technologies, but not all chatbots are considered conversational AI.   

Building a conversational AI chatbot requires an understanding of NLP, machine learning, and other AI technologies, as well as a well-defined use case and set of tasks for the chatbot to perform. There are various software and tools available to help with the development process.  

Identifying Goals  

The identification of specific goals is a crucial first step in the development of a chatbot. It is important to consider what objectives the chatbot is intended to achieve, such as enhancing customer satisfaction, reducing resolution times, or providing proactive customer service. Establishing these goals will guide the development process and ensure that the chatbot is designed to meet the needs of both the business and its customers.  

A chatbot is an artificial intelligence-powered software program that can simulate conversation with human users. Unlike human customer service representatives, chatbots do not experience fatigue, take time off, or have limited availability, and are accessible 24/7. Engaging with a chatbot allows it to understand the user's needs and provide an effective and efficient experience.

Chatbots are a valuable tool for companies to provide quick and convenient communication with their customers. Many well-established companies, including Amazon and Facebook, have already implemented chatbots in their operations.  

Rules-based or Conversational AI Chatbots?  

Chatbots are a popular solution for automating customer service and sales tasks. There are two main types of chatbots: rule-based and conversational. Rule-based chatbots are programmed with a set of pre-determined responses, whereas conversational chatbots use natural language processing (NLP) to understand the context and intent behind a customer's query and generate an appropriate response.

The operation of rule-based chatbots is based on a set of predefined rules to respond to user input. These chatbots rely on a simple decision tree structure, which means that specific questions have fixed answers, and the responses can be repetitive. Rule-based chatbots have the significant limitation of not being able to respond to synonyms of the questions they were trained on. To respond to customer inquiries, companies must manually provide a response for every possible scenario. This approach can be time-consuming and ineffective in providing accurate answers.  

Conversational AI chatbots, on the other hand, require a conversational interface, often represented as a conversation tree that maps out the different possible responses based on customer input. This allows the chatbot to handle a wider range of customer queries and improve customer satisfaction by providing quick and relevant responses.  

One common application of these types of solutions is as support chatbots, which are accessible through online devices, contact center answers and routing, or messaging apps. These chatbots can assist customers with product or service information and answer questions more efficiently than human customer service agents.

Do All Chatbots Use Conversational AI?  

The term "conversational AI" refers to a type of technology that aims to generate human-like conversation through the use of artificial intelligence. While the definition of AI itself is subjective, conversational AI typically encompasses a broader scope compared to chatbots, which primarily focus on automating specific tasks. Both chatbots and conversational AI can utilize natural language processing (NLP) to enhance their capabilities. They find application in various industries such as customer support, lead generation, e-commerce, and more. Businesses of different sizes can leverage conversational AI and NLP through chatbot development platforms. These platforms provide a comprehensive solution for building and managing chatbots that can recognize human language and respond in a natural manner. However, not all chatbots are considered to be conversational AI, as they may be more like advanced FAQs or searchable knowledge management systems and not able to address more ambiguous issues that require the use the latest machine learning algorithms or natural language processing.  

How To Build A Conversational AI Chatbot  

Building a conversational AI system is a complex and resource-intensive process that involves the use of machine learning algorithms, natural language processing, and chatbot frameworks. It typically requires a team of experienced developers with expertise in these areas to train the AI engine and build a functional system. However, pre-built chatbot software is available that can streamline the development process and make it easier for businesses to implement conversational AI in their operations. By providing methods for accessing and ingesting subject matter content efficiently, these modular software solutions offer a user-friendly interface that requires little to no coding and enables users to build a conversational AI agent within minutes.  

It is also possible to develop chatbots without the use of conversational AI. In this case, the chatbot operates based on pre-defined rules and scripts rather than through advanced AI algorithms. Depending on the layers of decision branching, chatbot development using such frameworks or APIs can be completed quickly and requires limited technical expertise, making it a more accessible solution for businesses.  

Why Reinvent the Wheel?  

One problem with building and maintaining NLP infrastructure becomes readily apparent to any individual or organization that decides to undertake such a task is that this is no small or inexpensive endeavor. On the contrary, developing NLP capabilities can be a long, arduous and expensive proposition. And while NLP offers significant advantages to any business, many companies are simply better off saving time and money by buying an off-the-shelf solution for NLP systems.  

This is where Soffos comes in. The Soffos Platform was designed to bring the industry’s best NLP capabilities to the market for the most competitive price available. With our cutting-edge and constantly evolving repertoire of APIs, Soffos is the solution for businesses looking for an easy to use, affordable yet extremely capable NLP AI. Soffos' modular framework makes it easy for non-AI software developers to empower their applications with highly functional and scalable NLP technologies enabling them with capabilities previously limited to AI engineers.

Low-code, Pro-code, & No-code  

Building a chatbot can be accomplished using several approaches, including low code, building from scratch, or using a no-code platform. Creating a chatbot from scratch offers greater customization capabilities, but requires a significant investment of time and resources, including a proficient understanding of software terminology and development skills.  

In contrast, low-code and no-code platforms provide quicker implementation, allowing businesses to create chatbots without needing extensive technical knowledge. The trend towards these platforms has been growing, as they offer an efficient way to reduce development time and investment costs.  

Final Words  

Chatbots have gained significant popularity in recent times as a tool for streamlining business operations and improving customer experience. They are capable of interacting with users, addressing their queries, and providing information, among other functions. Implementing chatbots in a business can lead to cost savings, improved customer service, and increased customer satisfaction. Given their potential benefits, businesses that have not yet adopted chatbots may want to consider their use.  

Chatbots are entering a new era. While they currently lack the full range of sophistication for managing the nuances of complex human conversation, the technology is advancing rapidly, and businesses need a platform that can evolve with these changes. Both Rule-based and NLP AI chatbots still lack true connections with the user. Advancements today indicate these limitations are becoming issues of the past, and very soon NLP AI chatbots will be conducting deep conversations to help find the answers businesses need.

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