Conversational AI Platform

- to BOTwiki - The Chatbot Wiki

Conversational AI Platforms, also known as Conversational Platform, Conversational Middleware, are software systems with the help of which you can chatbotsVirtual Assistants and Conversational User Interfaces for a wide variety of applications. Furthermore, they enable integration into chat interfaces such as messenger services, social media, SMS and chats on websites. A Conversational Platform usually has a developer interface (API) so that third parties can add their own customizations to the platform. [1]

The terms Conversational AI Platform and Conversational Platform are not clearly defined scientifically. Rather, they are services or platforms that use Natural Language Processing (NLP) as a basic technology and thus make various types of conversational interfaces realizable.


functional areas

In order to enable companies to develop and successfully operate chatbots and to constantly adapt them to the needs of users, a suitable Conversational Platform must cover many different functional areas. This is the processing of natural language, various integration possibilities and operation functionalities. A common architecture of the current Conversational Platforms is shown in the following figure. [1]

Conversational AI Platform

Source: Gartner - Market Guide for Conversational Platforms [1]

natural language processing

Currently, the Conversational AI Platform providers focus on the functional area NLP and thus on the interpretation and processing of natural language and the provision of a suitable answer for users. Successful providers in this area are Google with Dialogflow, Microsoft with LUIS, IBM with Watson, Amazon with Lex and Rasa with their open source solution. This form of system usually covers only a part of a Conversational Platform and is also called NLP service. Many of these services are SaaS (Software as a Service) solutions that are provided in conjunction with our own cloud solutions. [1]

Integrations and Middleware

As technology evolves, companies demand standardized and flexible integrations. On the one hand, simple and intelligent integrations in messenger interfaces such as WhatsApp, Facebook Messenger, Slack, Microsoft Teams, SMS and web chats are made possible. On the other hand, standardized integrations in enterprise software such as SAP, Salesforce, Hubspot, G Suite, Outlook, Workday, etc. are becoming increasingly important in order to optimally integrate chatbots into the business processes of companies. Currently, providers such as Kore.AI and BOTfriends to this functional area. It is assumed that the market for Conversational Platforms will be divided in the future into providers that focus predominantly on Natural Language Processing and providers that focus on simple integration options and functionalities for the operation of chatbots. [1]

Functions in the Chatbot Operations

Complementary functionalities, which make it possible to successfully operate, maintain and constantly develop chatbots in companies, are becoming more and more important. The reason for this is that the task of running chatbots is gradually being shifted away from IT departments to individual departments. This requires simple and intuitive user interfaces.

Some examples of these functionalities are:

  • Human handover tools that allow chatbots and human agents to work together to answer customer queries.
  • Simple Conversation Editor systems, which allow IT laymen to easily customize the content of chatbots.
  • Analytics Tools to measure the performance of chatbots and better tailor content to customer needs.
  • Training tools to constantly increase the knowledge base of chatbots so that they can provide appropriate answers to more requests.
  • Libraries of pre-built intents (questions and answers) and processes for a wide variety of applications and industries, enabling you to create chatbots very quickly and easily.

Scalability and Flexibility

To build a holistic, scalable and sustainable Conversational AI platform, many companies are currently developing their own Conversational Middleware platforms. These make it possible to connect various services and software systems in such a way that all necessary functional areas are sufficiently covered and the services used can be easily exchanged. With this approach, companies will be able to integrate new and better performing services into their chatbot architecture in the future. Outdated and cost-intensive services can thus be eliminated. In this way, companies always stay up to date. At the moment, technology providers are also emerging that offer Conversational Middleware platforms as a product. [1]

> Back to the BOTwiki - The Chatbot Wiki